JP2006005680A - Image processing apparatus, image reading apparatus, image forming apparatus, and color copying apparatus - Google Patents

Abstract

An image processing apparatus that detects characters in image data and performs appropriate image processing, an image reading apparatus including the image processing apparatus, an image forming apparatus including the image processing apparatus, and the image processing apparatus A color copying apparatus including the above is provided.
By determining whether a character is a pixel of interest by referring to the state of an image of surrounding pixels, it is possible to determine whether the character is in a size image area. Further, when a halftone dot separation result (printed matter), a color determination result (color), or a gray determination result (printing paper photograph) is made around the peripheral pixels of the high density data, it is not determined that the character is a character. In addition, when there is no halftone dot separation result (printed material), color determination result (color), gray determination result (printing paper photograph) around the altitude data, and there is a character edge, it is determined whether the character is a character. The halftone dot separation result is referred to in order to prevent erroneous determination of a dark black portion in the halftone dot of the printed matter. The reason for referring to the gray determination result is to prevent erroneous determination of a dark portion of the photographic paper photograph. As described above, it is possible to accurately determine the character by referring to the adjacent area of the high density area.
[Selection] Figure 1

Description

  The present invention relates to an image processing apparatus that detects characters in image data and performs appropriate image processing, an image reading apparatus including the image processing apparatus, an image forming apparatus including the image processing apparatus, and the image processing The present invention relates to a color copying apparatus provided with the apparatus.

  The following inventions have been proposed as techniques for detecting characters in image data and performing appropriate image processing on the character regions.

  Patent Document 1 proposes an image processing apparatus that can improve the image reproduction quality of characters and reproduce characters clearly.

  In Patent Document 2, a black character is reproduced only with a black color material, the image quality of the black character is improved, and a misidentification that identifies an area other than the black character of the original image as a character portion is reduced, thereby improving the original image with high image quality. An image processing apparatus and a digital color copying apparatus have been proposed.

  In Patent Document 3, by detecting only an edge of a character part by detecting an edge pair corresponding to a stroke constituting the character, only the edge of the character part is detected accurately and suitable for the character part. A character part detection method and an image processing apparatus for performing image processing have been proposed.

  Patent Document 4 proposes an image processing apparatus that can identify not only the outline of a character but also the inside to improve the quality of the character.

  Patent Document 5 proposes an image processing apparatus, an image forming apparatus, an image processing apparatus, and an image forming apparatus that identify not only the outline portion of a character (line drawing) but also the inside thereof to improve the image quality of the character (line drawing). Yes.

  In Patent Document 6, an image processing apparatus, an image output apparatus, an image processing method, and an image that maintain high image quality and prevent white spots when outputting an image in which a character area and a picture area are mixed are disclosed. A recording medium on which a processing program is recorded has been proposed.

In Patent Document 7, character processing is performed on the middle and lower-case letters in high-density thick characters, and gradation processing is performed on the high-density back surface, thereby eliminating the problems of conventional image area identification and realizing high image quality. In addition, an original reading apparatus employing an image area identification circuit capable of improving character reproducibility has been proposed.
JP 2001-268383 A JP-A-11-215368 JP 2001-52186 A JP 2000-156780 A JP-A-11-205607 Japanese Patent Laid-Open No. 11-146195 Japanese Patent Laid-Open No. 7-95397

  However, the above invention has the following problems.

  In the above invention, when detecting a character, it is not possible to detect whether the pixel of interest belongs to a picture region or a high-density region belonging to a region of a character in several pixels around the pixel of interest. In addition, it is easy to erroneously determine a character such as a Gothic character in order to detect a thin line. Further, no erroneous determination occurs in a halftone dot pattern, but an erroneous determination occurs in a pattern that does not have a halftone dot such as a photographic paper photograph.

  In the above invention, the character edge is used as a trigger to detect the inside of the character (hereinafter referred to as a character) based on the high density area and the halftone dot. Easy to do. In addition, since an area within a character is detected based only on the character edge information and the image quality of the black area, erroneous determination is easy.

  Therefore, the present invention provides an image processing apparatus and an image reading device that can detect characters with high accuracy by detecting a halftone dot that expresses a gradation by the area of a dot and an intermediate density region that expresses the magnitude of density. An object of the present invention is to propose an apparatus, an image forming apparatus, and a color copying apparatus.

  According to a first aspect of the present invention, there is provided an image processing apparatus that performs a predetermined process on input image data and outputs the image data, a character edge area detection unit that detects a character edge area of the image data, Medium density area detecting means for detecting a medium density area; expansion means for expanding the medium density area detected by the medium density area detecting means; picture area detecting means for detecting a picture area of the image data; It is determined whether or not the image data has characters from a character edge region detection result by the character edge region detection unit, a medium density region detection result by the medium density region detection unit, and a design region detection result by the design region detection unit. A character determination means; an expansion processing means for expanding the medium density area detected by the medium density area detection means; Detected by the color determination means for determining the color of the image, the determination result by the character determination means, the determination result by the color determination means, the intermediate density area detected by the intermediate density area detection means, and the pattern area detection means And determining means for determining whether or not the image data is in a character by the pattern area.

  According to a second aspect of the present invention, in the image processing apparatus according to the first aspect, the picture area detecting unit detects a halftone dot from the image processing target area, and the image processing is performed when the halftone dot is not detected. It is determined that the pattern area is not included in the target area, and when the halftone dot is detected, it is determined that the pattern area is included in the image processing target area.

  According to a third aspect of the present invention, in the image processing apparatus according to the first or second aspect, the character edge region detecting means detects a character on a white background.

  According to a fourth aspect of the present invention, in the image processing apparatus according to any one of the first to third aspects, the medium density area detecting means includes a high density area detecting means for detecting a high density area from the image data, and It has a gray pixel detecting means for detecting a gray pixel from the image data, and a white area detecting means for detecting a white area from the image data.

  According to a fifth aspect of the present invention, in the image processing apparatus according to any one of the first to fourth aspects, the determination unit detects the high density region of a predetermined number of pixels or more by the high density region detection unit. The image data is determined not to be in the character.

  An image reading apparatus according to claim 6 is an image processing apparatus according to any one of claims 1 to 5, and a reading means for inputting image data generated by color-separating and reading an original image to the image processing apparatus. It is characterized by having.

  According to a seventh aspect of the present invention, there is provided an image forming apparatus that forms an image based on the image processing apparatus according to any one of the first to fifth aspects and image data output from the image processing apparatus. And image output means for outputting an image formed on a sheet.

  The color copying apparatus according to claim 8 is an image processing apparatus according to any one of claims 1 to 5, and reading means for inputting image data generated by color-separating and reading a document image to the image processing apparatus. And image output means for forming an image based on the image data output from the image processing apparatus, forming the formed image on a sheet, and outputting the image.

  According to a ninth aspect of the present invention, the color copying apparatus according to the eighth aspect further comprises control means for analyzing a print instruction command from the outside and printing out image information input from the outside by the image output means. It is characterized by being.

  The present invention determines whether or not the high density area belongs to the character by the medium density area, the character edge area, the halftone dot area, and the color area adjacent to the high density area in the image data. Can detect characters.

  According to the present invention, it is possible to determine the character in the size image area by referring to the state of the image of the peripheral pixel and determining whether the character is the pixel of interest. Further, when the result of halftone dot separation (printed matter), color determination result (color), and gray determination result (printing paper photograph) is set around the peripheral pixels of the high density data, it is not determined as a character.

  Hereinafter, an image processing apparatus of the present invention will be described in detail with reference to the drawings.

<Digital full color copier>
FIG. 1 is a schematic configuration diagram of a digital full-color copying machine including an image processing apparatus according to the present embodiment.

  The digital full-color copying machine according to the present embodiment includes a color image reading device (hereinafter referred to as a scanner) 200 and a color image recording device (hereinafter referred to as a color printer) 400.

  The scanner 200 forms an image of the document 150 on the contact glass 202 on the color sensor 207 via the illumination lamp 205, the mirror groups 204A, 204B, and 204C, and the lens 206, and converts the color image information of the document into, for example, Each color separation light of blue (hereinafter referred to as B), green (hereinafter referred to as G) and red (hereinafter referred to as R) is read and converted into an electrical image signal. In this embodiment, the color sensor 207 is composed of a three-line CCD sensor, and reads B, G, and R images for each color. Based on the color separation image signal intensity levels of B, G, and R obtained by the scanner 200, color conversion processing is performed by an image processing unit (not shown) to obtain black (hereinafter referred to as Bk), cyan (hereinafter referred to as “black”). C), magenta (hereinafter referred to as “M”), and yellow (hereinafter referred to as “Y”) color image data including recording color information is obtained.

  Using this color image data, the color printer 400 superimposes Bk, C, M, and Y images on the intermediate transfer belt and transfers them onto transfer paper. Upon receiving a scanner start signal that takes the operation and timing of the color printer 400, the scanner 200 scans the original in the direction of the left arrow by an illumination / mirror optical system including illumination lamps and mirror groups 204A, 204B, and 204C. One color image data is obtained for each scan. Each time, the color printer 400 sequentially visualizes the images and superimposes them on the intermediate transfer belt to form a full-color image of four colors.

  A writing optical unit 401 as an exposure unit of the color printer 400 converts the color image data from the scanner 200 into an optical signal, performs optical writing corresponding to the original image, and forms an electrostatic latent image on the photosensitive drum 414. Form. The optical writing optical unit 401 includes a laser light emitter 441, a light emission drive control unit (not shown) that drives the light emission, a polygon mirror 443, a rotation motor 444 that rotationally drives it, an fθ lens 442, a reflection mirror 446, and the like. Has been. The photosensitive drum 414 rotates counterclockwise as shown by the arrow. Around the photoconductive drum 414, a photoconductor cleaning unit 421, a static elimination lamp 414M, a charger 419, a potential sensor 414D for detecting a latent image potential on the photoconductor drum, and a developing device selected from the revolver developing device 420. A development density pattern detector 414P, an intermediate transfer belt 415, and the like are disposed.

  The revolver developing device 420 includes a BK developing unit 420K, a C developing unit 420C, an M developing unit 420M, a Y developing unit 420Y, and a revolver rotation driving unit (not shown) that rotates each developing unit in a counterclockwise direction as shown by an arrow. ) Etc. Each of these developing units brings developer spikes into contact with the surface of the photosensitive drum 414 in order to visualize the electrostatic latent image. Each developing device includes a rotating developing sleeve 420KS, 420CS, 420MS, 420YS and a developing paddle that rotates to assemble and agitate the developer. In the standby state, the revolver developing device 420 is set at a position where development is performed by the BK developing unit 420K. When the copying operation is started, the scanner 200 starts reading BK image data from a predetermined timing. Based on the data, optical writing and latent image formation by laser light are started. Hereinafter, an electrostatic latent image based on Bk image data is referred to as a Bk latent image. The same applies to C, M, and Y image data. In order to enable development from the leading edge of the Bk latent image, before the leading edge of the latent image reaches the developing position of the Bk developing unit 420K, the rotation of the developing sleeve 420KS is started to develop the Bk latent image with Bk toner. . Thereafter, the developing operation of the Bk latent image area is continued. However, when the trailing edge of the latent image passes the Bk latent image position, the developing operation of the next color from the developing position by the Bk developing unit 420K is promptly performed. The revolver developing device 420 is driven and rotated to the position. This rotation operation is completed at least before the leading edge of the latent image by the next image data arrives.

  When the image forming cycle is started, the photosensitive drum 414 rotates counterclockwise as indicated by an arrow, and the intermediate transfer belt 415 rotates clockwise by a drive motor (not shown). As the intermediate transfer belt 415 rotates, BK toner image formation, C toner image formation, M toner image formation, and Y toner image formation are sequentially performed. Finally, intermediate transfer is performed in the order of BK, C, M, and Y. A toner image is formed over the belt 415. The BK image is formed as follows. That is, the charger 419 uniformly charges the photosensitive drum 414 to about −700 V with a negative charge by corona discharge. Subsequently, the laser diode 441 performs raster exposure based on the Bk signal. When the raster image is exposed in this way, the charge proportional to the exposure light amount disappears in the exposed portion of the uniformly charged photosensitive drum 414, and an electrostatic latent image is formed. The toner in the revolver developing device 420 is negatively charged by stirring with the ferrite carrier, and the BK developing sleeve 420KS of the developing device is connected to a metal base layer of the photosensitive drum 414 by a power supply circuit (not shown). It is biased to a potential in which a negative DC potential and an AC are superimposed. As a result, toner does not adhere to the portion where the charge of the photosensitive drum 414 remains, and Bk toner is adsorbed to the portion without charge, that is, the exposed portion, and Bk visible similar to the latent image. An image is formed. The intermediate transfer belt 415 is stretched around a drive roller 415D, a transfer counter roller 415T, a cleaning counter roller 415C, and a driven roller 415F, and is rotated by a drive motor (not shown). Now, the Bk toner image formed on the photosensitive drum 414 is applied to a belt transfer corona discharger (hereinafter referred to as a belt transfer unit) 416 on the surface of an intermediate transfer belt 415 that is driven at a constant speed in contact with the photosensitive member. Is transcribed by. Hereinafter, toner image transfer from the photosensitive drum 414 to the intermediate transfer belt 415 is referred to as belt transfer. Some untransferred residual toner on the photoconductor drum 414 is cleaned by the photoconductor cleaning unit 421 in preparation for reuse of the photoconductor drum 414. The toner collected here is stored in a waste toner tank (not shown) via a collection pipe.

  In addition, on the intermediate transfer belt 415, Bk, C, M, and Y toner images sequentially formed on the photosensitive drum 414 are sequentially aligned on the same surface to form a four-color superimposed belt transfer image. Thereafter, batch transfer is performed on the transfer paper by a corona discharge transfer device. By the way, on the photosensitive drum 414 side, the process proceeds to the C image forming process after the BK image forming process. At a predetermined timing, reading of C image data by the scanner 200 starts, and laser light writing by the image data is performed. Then, a C latent image is formed. The C developing unit 420C rotates the revolver developing device after the previous Bk latent image rear end portion passes through the developing position and before the C latent image leading end reaches, Develop the image with C toner. Thereafter, the development of the C latent image area is continued, but when the trailing edge of the latent image passes, the revolver developing device 420 is driven in the same manner as in the previous Bk developing device, and the C developing device 420C is sent out. The M developing device 420M is positioned at the developing position. This operation is also performed before the leading edge of the next M latent image reaches the developing unit. It should be noted that the image forming process for each of the M and Y images will not be described because the operations of reading the respective image data, forming the latent image, and developing are in accordance with the aforementioned Bk image and C image processes.

  The belt cleaning device 415U includes an inlet seal, a rubber blade, a discharge coil, and a contact / separation mechanism for the inlet seal and the rubber blade. During belt transfer of the second, third, and fourth color images after the first color Bk image is transferred to the belt, the blade seal mechanism separates the inlet seal, rubber blade, and the like from the intermediate transfer belt surface. deep.

  A paper transfer corona discharger (hereinafter referred to as a paper transfer unit) 417 is a corona discharge method for transferring the superimposed toner image on the intermediate transfer belt 415 to the transfer paper. Apply to transfer belt.

  The transfer paper cassette 482 in the paper supply bank stores transfer papers of various sizes, and is fed in the direction of the registration roller pair 415R by the paper supply roller 483 from the cassette storing the paper of the specified size.・ Conveyed. Reference numeral 412B2 denotes a paper feed tray for manually feeding OHP paper, cardboard, or the like. The transfer paper is fed from one of the paper feed trays at the timing at which image formation is started, and stands by at the nip portion of the registration roller pair 415R. Then, when the leading edge of the toner image on the intermediate transfer belt 415 approaches the paper transfer unit 417, the registration roller pair 415R is driven so that the leading edge of the transfer paper coincides with the leading edge of the image, and the alignment between the paper and the image is performed. Done. In this way, the transfer paper is superimposed on the color superposition image on the intermediate transfer belt and passes over the paper transfer device 417 connected to a positive potential. At this time, the transfer paper is charged with a positive charge by the corona discharge current, and most of the toner image is transferred onto the transfer paper. Subsequently, when the paper passes through a separation static eliminator (not shown) disposed on the left side of the paper transfer unit 417, the transfer paper is neutralized, separated from the intermediate transfer belt 415, and transferred to the paper conveyance belt 422. The transfer paper onto which the four-color superimposed toner images have been transferred from the intermediate transfer belt surface is conveyed to the fixing device 423 by the paper conveying belt 422, and the toner is transferred to the nip portion between the fixing roller 423A and the pressure roller 423B controlled to a predetermined temperature. The image is melted and fixed, sent out of the main body by a pair of discharge rollers 424, and stacked face up on a copy tray (not shown).

  The surface of the photosensitive drum 414 after the belt transfer is cleaned by a photosensitive member cleaning unit 415U including a brush roller, a rubber blade, and the like, and is uniformly discharged by a discharging lamp 414M. The intermediate transfer belt 415 after transferring the toner image to the transfer paper again cleans the surface by pressing the blade with the blade contact / separation mechanism of the cleaning unit 415U. In the case of repeat copying, the operation of the scanner and the image formation on the photosensitive member are continued to the fourth color image process for the first sheet, and then proceed to the first color image process for the second sheet at a predetermined timing. In the intermediate transfer belt 415, the second Bk toner image is belt-transferred to the area where the surface is cleaned by a belt cleaning device following the batch transfer process of the first four-color superimposed image to the transfer paper. So that After that, the operation is the same as the first sheet.

  The digital full color copying machine shown in FIG. 1 can print out (image output) with a color printer 400 when print data is given from a host such as a personal computer through a LAN or parallel I / F, and a scanner. This is a color copying machine with a composite function capable of transmitting the image data read in 200 to a remote facsimile and printing out the received image data. This copier is connected to a public telephone network via a private branch exchange PBX, and can communicate with a facsimile server or a service center management server via the public telephone network.

<Electrical system>
<< Outline of System >> FIG. 2 shows an outline of the electrical system of the digital full-color copying machine according to the present embodiment. FIG. 2 illustrates a control device for a digital full-color copying machine with the main controller 10 as the center. The main controller 10 controls the entire copying machine. The main controller 10 includes a display for an operator, an operation / display board OPB for performing function setting input control from the operator, an editor 15, a scanner 200, and optional ADF control, control for writing a document image in an image memory, and image Charge, exposure, development, paper feed, transfer, fixing, and transfer in the scanner controller 12, the printer controller 16, the image processing unit (IPU) 300, and the color printer 400 that control the image formation from the memory. A distributed control device such as an engine controller 13 for controlling an image forming engine for carrying paper is connected. Each distributed control device and the main controller 10 exchange machine states and operation commands as necessary. A main motor and various clutches necessary for paper conveyance and the like are also connected to a driver (not shown) in the main controller 10. In addition, 11 is an IC card and 14 is a sorter controller. The IC card 11 is used for managing the number of copies for each department, for example.

  The color printer 400 includes an electric circuit and a control circuit for driving a mechanism element that performs feeding of a photoconductor 414, image exposure by a laser writing unit, development, transfer, fixing, and paper discharge as well as feeding from a paper feed tray. , And various sensors are provided.

  The printer controller 16 analyzes an image from the outside such as a personal computer and a command for instructing printing, develops a bitmap as image data into a printable state, and drives the printer 400 via the main controller 10 to print the image data. Out. A LAN control 19 and a parallel I / F 18 are provided to receive and operate images and commands via the LAN and parallel I / F.

  When there is a facsimile transmission instruction, the FAX controller 17 drives the scanner 200 and the IPU 300 via the main controller 10, reads the image of the document, and sends the image data to the facsimile communication line via the communication control 20 and the PBX. When a facsimile call is received from the communication line and image data is received, the printer 400 is driven via the main controller 10 to print out the image data.

  FIG. 3 shows the configuration of the image processing unit (IPU) 300. In the figure, R, G, B image data output from the scanner 200 is given to the IPU 300 via the interface (1) 351. It should be noted that when the BR unit 356 instructs B or R monochrome recording, R, G, and B image data are selected and assembled, but description of image recording processing in this mode is omitted. The R, G, B image data given to the IPU 300 is converted from reflectance data (R, G, B data) to density data (R, G, B data) by the RGBγ correction unit 310.

  Based on the density R, G, B data, the document recognition unit 320 determines that the image area to which the data is addressed is a character area (character or line drawing area) or a picture area (photo or picture area & not a character area). And the C / P signal and the B / C signal are supplied to the main controller 10 via the RGB filter unit 330 and the interface (3) 353. The C / P signal is a C / P signal: a 2-bit signal, 2 is a character area, 1 is a character edge area, and 0 is a picture area.

  The B / C signal is a B / C signal: a 1-bit signal, where H (“1”) indicates an achromatic region and L (“0”) indicates a chromatic region.

  << Document Recognition Unit 320 (FIG. 4) >> FIG. 4 shows functions of the document recognition unit 320 in block sections. The document recognition unit 320 performs character edge detection, pattern detection, and chromatic / achromatic detection, and outputs a C / P signal representing a character edge area or a pattern area and a B / C signal representing a chromatic area / achromatic area. appear.

  The document recognition unit 320 is roughly divided into a filter unit 321, an edge extraction unit 322, a white region extraction unit 323, a halftone dot extraction unit 324, a color determination unit 325, and an overall determination unit 326. Here, a case where the reading density of the scanner 200 is about 600 dpi will be described as an example.

  << Filter Unit 321 >> The filter unit 321 corrects the G image data generated by the scanner 200 mainly for extracting the edge of the character. Here, since the data read by the scanner 200 may be blurred due to the performance of a lens or the like, an edge enhancement filter is applied. Here, it is necessary to simply emphasize the edge on the original and not to emphasize the line pattern for gradation expression that is widely used in copying machines. If the line pattern is emphasized, it is necessary to extract the picture (gradation expression area by the line pattern) as an edge and eventually misidentify it as a character edge. is there. Also, as shown in FIG. 8, the 600 dpi line pattern A and the 400 dpi line pattern B have different repetition periods, so it is difficult to avoid enhancement with the same filter coefficient. Therefore, the cycle of the image pattern is detected and the filter coefficient is switched. In FIG. 8, the sum of the width of one white block in the main scanning direction x and the width of one black block adjacent thereto is a line pitch (constant width: a predetermined number of pixels), that is, a line cycle, and a low density halftone. In this case, the white block width is widened and the black block width is narrowed. As the density becomes higher, the white block width becomes narrower and the black block width becomes wider.

  In this embodiment, the filter unit 321 has a pixel matrix of 7 pixels in the main scanning direction x × 5 pixels in the sub-scanning direction y (mechanical document scanning direction of the scanner 200). As shown in the block, there are two sets of coefficient groups (coefficient matrices) A and B addressed to each pixel, each weighted coefficient a1 to a7, b1 to b7, c1 to c7, d1 to d7, and e1 to e7. . The next coefficient group A is a filter processing coefficient that suppresses emphasis of the 600 dpi line pattern A shown in FIG. 8 and emphasizes the edge of the character. The coefficient group B is a 400 dpi line shown in FIG. This is a filter processing coefficient that suppresses emphasis of the pattern B and emphasizes the edge of the character.

Coefficient group A
0 -1 0 -2 0 -1 0
0 -1 0 -2 0 -1 0
0 -1 -1 20 -1 -1 0
0 -1 0 -2 0 -1 0
0 -1 0 -2 0 -1 0

Coefficient group B
-1 0 0 -2 0 0 -1
-1 0 0 -2 0 0 -1
-1 0 -1 20 -1 0 -1
-1 0 0 -2 0 0 -1
-1 0 0 -2 0 0 -1

  Note that the horizontal direction is the alignment in the main scanning direction x, and the vertical direction is the alignment in the sub-scanning direction y. The coefficients in the first row of the coefficient groups A and B are the coefficients a1 to a7 in the first row of the coefficient matrix of the block of the filter 321 in FIG. The center “20” is the coefficient of the pixel in the center of the third row c1 to c7 of the coefficient matrix of the block of the filter unit 321, that is, the coefficient c4 of the target pixel. The sum (product sum value) of the products (total 7 × 5 = 35) obtained by multiplying each coefficient of the coefficient matrix by the value represented by the image data of the pixel addressed to it is divided by 16, and the target pixel is added by adding the target pixel. Make corrections. The image data value processed by the filter unit 321 of the target pixel (pixel addressed to c4) is given to the edge extraction unit 322 and the white area extraction unit 323. Here, the pixel of interest is a pixel that is currently processed, and it is updated to pixels that are sequentially different in the x direction and in the y direction.

  In the coefficient group A, a negative coefficient (small value coefficient) is distributed at the line pitch of the 600 dpi line pattern A shown in FIG. 8, and 0 (slightly large coefficient) is distributed between them, and the edge For emphasis, 20 (very large coefficient) is assigned to the target pixel. As a result, when the image data (target pixel) is the black / white edge of the line pattern A region, the weighted average value (product sum value) derived therefrom is the character edge that is not the line pattern A. Compared to a certain time, the value is considerably lower.

  In the coefficient group B, negative coefficients (small value coefficients) are distributed at the line pitch of the 400 dpi line pattern B shown in FIG. 8, and 0 (slightly large coefficient) is distributed between them, and For the edge enhancement, 20 (very large coefficient) is assigned to the target pixel. As a result, when the image data (target pixel) is the black / white edge of the line pattern B region, the weighted average value (product sum value) derived therefrom is the character edge that is not the line pattern B. Compared to a certain time, the value is considerably lower.

The filter unit 321 performs the filter processing by the coefficient group B when either of the following conditions 1 and 2 is satisfied, that is, when there is a high possibility that the line pattern B is 400 dpi in FIG. Sometimes filter by coefficient group A:
-Condition 1- [Condition to see if the 400 dpi line pattern B is thin (white section in FIG. 8)]
(D [3] [1] <D [3] [2]) &
(D [3] [7] <D [3] [6]) &
(ABS (D [3] [2] -D [3] [4])> ABS (D [3] [4] -D [3] [1])) &
(ABS (D [3] [6] -D [3] [4])> ABS (D [3] [4] -D [3] [7]))
-Condition 2-[Condition to see if the 400 dpi line pattern B is dark (black section in FIG. 8)]
(D [3] [1]> D [3] [2]) &
(D [3] [7]> D [3] [6]) &
(ABS (D [3] [2] −D [3] [4])> ABS (D [3] [4] −D [3] [1])) &
(ABS (D [3] [6] -D [3] [4])> ABS (D [3] [4] -D [3] [7]))
Note that D [i] [j] means a value represented by image data of a pixel at a position of x = i, y = j on a pixel matrix of x, y distribution, for example, D [3] [1 ] Is a value represented by image data of a pixel to which the coefficient a3 of the coefficient matrix shown in the block of the filter unit 321 in FIG. 4 is addressed. “&” Means “logical product: AND”, and “ABS” means an absolute value operator. The target pixel is D [4] [3].

  When the condition 1 or 2 is established, the pixel of interest at that time is subjected to the filter processing for character edge emphasis using the coefficient group B, assuming that the pixel of interest is in the 400 dpi line pattern pattern B area at the time of 600 dpi reading shown in FIG. If neither of the conditions 1 and 2 is satisfied, the character edge emphasis filter process is performed using the coefficient group A that avoids emphasizing the 600 dpi line pattern A at the time of 600 dpi reading shown in FIG. That is, the image period (pitch) is detected so that the image pattern of a specific period is not emphasized. It is possible to emphasize the edge of a character without emphasizing the line pattern. FIG. 4 shows an aspect in which G image data is referred to for edge processing, but it is not limited to G image data, and may be luminance data. Any signal expressing darkness can be applied.

<Edge extraction>
<< Edge Extraction Unit 322 >> The character region has many high-level density pixels and low-level density pixels (hereinafter referred to as black pixels and white pixels), and these black pixels and white pixels are continuous in the edge portion. is doing. The edge extraction unit 322 detects a character edge based on the continuity of each of such black pixels and white pixels.

<< Ternization Unit 322a >> First, G image data (input data of the edge extraction unit 322) in which the filter unit 321 uses the two threshold values TH1 and TH2 to perform the filter processing for character edge enhancement in the ternization unit 322a. ). For example, when the image data represents 256 gradations (0 = white) from 0 to 255, the thresholds TH1 and TH2 are set to TH1 = 20 and TH2 = 80, for example. In the ternary unit 322a,
Input data <TH1
The input data is converted into ternary data representing pixels to which the data is addressed as white pixels,
TH1 ≦ input data <TH2
Is converted to input ternary data representing halftone pixels,
When TH2 ≦ input data, the input data is converted into ternary data representing black pixels.

  << Black Pixel Continuous Detection Unit 322b, White Pixel Continuous Detection Unit 322c >> Black Pixel Continuous Detection Unit 322b and White Pixel Continuous Detection Unit 322c are locations where black pixels are continuous and white pixels are continuous based on the ternary data Are detected by pattern matching. In this embodiment, the pattern matching uses patterns BPa to BPd and WPa to WPd of a 3 × 3 pixel matrix shown in FIG. In the pattern shown in FIG. 9, black circles indicate the above-described black pixels, white circles indicate the above-described white pixels, and blank pixels without any of the circles are black pixels, halftone pixels, white pixels It does not matter whether it is any of the above. The pixel at the center of the 3 × 3 pixel matrix is the target pixel.

  When the distribution of the content of the ternary data matches any of the black pixel distribution patterns BPa to BPd shown in FIG. 9, the black pixel continuous detection unit 322b represents the target pixel at that time as a “black continuous pixel”. Data is given to the pixel of interest. Similarly, when matching with any of the white pixel distribution patterns WPa to WPd shown in FIG. 9, the white pixel continuous detection unit 322c sets the target pixel at that time as “white continuous pixel” and gives data indicating the target pixel to the target pixel. .

  << Neighboring Pixel Detection Unit 322d >> The next neighboring pixel detection unit 322d is a black continuous pixel in the vicinity of the target pixel in the neighboring pixel detection unit 322d with respect to the detection results of the black pixel continuous detection unit 322b and the white pixel continuous detection unit 322c. Alternatively, it is determined whether the target pixel is in the edge region or the non-edge region by checking whether there is a white continuous pixel. More specifically, in the present embodiment, when one or more black continuous pixels and white continuous pixels exist in a 5 × 5 pixel matrix block, the block is defined as an edge region. If not, the block is determined as a non-edge region.

  << Isolated Point Removal Unit 322e >> Furthermore, since there are continuous character edges, the isolated point removal unit 322e corrects an isolated edge to a non-edge region. Then, an edge signal “1” (edge area) is output to a pixel determined as an edge area, and an edge signal “0” (non-edge area) is output to a pixel determined as a non-edge area.

<White area extraction>
<< White Region Extraction Unit 323 >> As shown in FIG. 21, the white region extraction unit 323 in FIG. 4 includes a binarization unit 323e, an RGB white extraction unit 323b, a white determination unit 323c, a white pattern matching unit 323d, and a white pattern correction unit. 323j, a white expansion unit 323k, a white contraction unit 323l, a white correction unit 323g, a gray pattern matching unit 323h, a gray expansion unit 323i, and a determination unit 323m. Note that the white region extraction unit 323 in FIG. 4 is obtained by replacing the portion M in FIG.

  << Binarization Unit 323e >> The binarization unit 323e binarizes the edge enhancement output of the image density data (G image data) of the filter unit 321 with the threshold value thwsb, and represents the processing of the white pattern matching unit 323d ( A binarized white determination signal for generating white data referred to in step S7) of FIG. 5 is generated. Note that the edge emphasis output is 256 gradations from 0 to 255 in this embodiment, 0 is white without density, an example of the threshold value thwsb is 50, and the value of the edge emphasis output is thwsb = 50. If smaller, the binarization unit 323e determines “binarized white” and generates a binarized white determination signal “1”. When the value of the edge emphasis output is thwsb = 50 or more, a binarized white determination signal “0” is generated.

<< RGB White Extraction Unit 323b >> The RGB white extraction unit 323b
1) RGB white background detection 2) Color background detection 3) Gray pixel detection is performed to determine whether the image data is a white area or a gray area (medium density area).

1) RGB White Background Detection In the RGB white background detection, the white background separation operation is activated by detecting a white background area from R, G, B image data. That is, the white background separation process is started. Specifically, as shown in the pattern WBP of FIG. 10, if all of the R, G, B image data of the 3 × 3 pixel matrix is smaller than the threshold thwss, the target pixel (the central pixel of the 3 × 3 pixel matrix) is determined. The white area is determined and the white pattern matching unit 323d (white background determination signal referred to in step S3 of FIG. 10 representing the processing) is activated (“1”). This is to detect whether there is a white pixel region of a certain extent. Each of the R, G, and B image data has 256 gradations from 0 to 255 in this embodiment, 0 is a base level without density, threshold thwss <thwsb, and an example of thwss is 40. If all of the R, G, B image data are smaller than thwss = 40, it is determined as “white background” and a white background determination signal “1” is generated. When any of the R, G, and B image data is thwss = 40 or more, a white background determination signal “0” is generated.

2) Color Background Detection Color background is detected so that a light color is not determined as a white background.
A) Here, first, assuming that the sign of each pixel of the 5 × 5 pixel matrix centered on the target pixel is shown in the pattern MPp of FIG. 11, the center pixel c3 that is the target pixel (X mark pixels of MCa to MCd) ) RGB difference (difference between the maximum and minimum values of R, G, B image data addressed to one pixel) is greater than the threshold thc, the color pixel determination signal a is set to “1” (color pixel), and the threshold thc In the following cases, “0” (monochrome pixel) is set.
B) If the R, G, B image data of any pixel in the peripheral pixel group Δ (in MCa to MCd in FIG. 11) on one side of the target pixel are all equal to or less than the threshold thwc, the one-side white determination signal b is “1” (white pixel), and “0” (non-white pixel) when the threshold value thwc is exceeded. The threshold thwc is 20, for example.
C) If the R, G, B image data of any pixel in the peripheral pixel group □ (in MCa to MCd in FIG. 11) on the other side of the target pixel is less than or equal to the threshold thwc, the other-side white determination signal c is “1” (white pixel), and “0” (non-white pixel) when the threshold value thwc is exceeded.
D) In any of the patterns MCa to MCd in FIG.
a AND (exclusive NOR of b and c) = "1"
That is, when a = “1” (the pixel of interest is a color pixel) and b and c match (a white pixel on both sides of the pixel of interest or a non-white pixel on both sides), The color background determination signal d is set to “1” (color background). This color ground determination signal d is referred to by the white pattern matching unit 323d (step S6 in FIG. 10 representing the processing).

  The above-described pattern matching A to D is performed because when a black character is slightly colored due to the RGB reading position shift, it is not picked up as a color. At a colored position around the black character, (exclusive NOR of b and c) or “0” (one pixel on both sides of the target pixel is a white pixel and the other is a non-white pixel). In this case, the color gamut determination signal d = “0” (non-colored background). In addition, when the pixel of interest is a color pixel whose periphery is surrounded by a white background, the color background determination signal d = “1” (color background), and even when the line is intricate, a light color pixel is detected as the color background. be able to. That is, when the line is intricate, the originally white portion is not completely read as white. When the RGB difference is small, the pixel is not determined as a color pixel. Therefore, the threshold thwc is set to be stricter than the white background for which the density is to be viewed (for example, thws = 20 for thwss = 40 and thwsb = 50). In this process, it is possible to accurately check whether the background is a white background and accurately detect a light color pixel as a color background.

In addition, in the case of color detection, valley white pixel detection may be performed. The valley white pixel detection detects valley white pixels in a small white area that cannot be detected by the RGB white background detection based on the 5 × 5 pixel matrix distributions RDPa and RDPb of the G image data shown in FIG. Specifically, based on the 5 × 5 pixel matrix distribution RDPa,
miny = min (G [1] [2], G [1] [3], G [1] [4], G [5] [2], G [5] [3], G [5] [4 ])
Is calculated. That is, the minimum density miny in the pixel group with black circles in the 5 × 5 pixel matrix distribution RDPa shown in FIG. 10 is extracted. And
maxy = max (G [3] [2], G [3] [3], G [3] [4])
Is calculated. That is, the maximum density maxy in the pixel group with white circles in the 5 × 5 pixel matrix distribution RDPa shown in FIG. 10 is extracted. next,
mint = min (G [2] [1], G [3] [1], G [4] [1], G [2] [5], G [3] [5], G [4] [5 ])
Is calculated. That is, the lowest density mint in the pixel group with black circles in another 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 is extracted. And
maxt = max (G [2] [3], G [3] [3], G [4] [3])
Is calculated. That is, the highest density maxt in the pixel group with white circles in the 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 is extracted. Here, min () is a function for detecting the minimum value. max () is a function for detecting the maximum value. next,
OUT = ((miny−maxy)> 0) # ((mint−maxt)> 0)
Is calculated. That is, of (miny-maxy) and (mint-maxt), the larger positive value is defined as a valley detection value OUT, and if the value of OUT is equal to or greater than a certain threshold, the target pixel (RDPa or RDPb Are detected as valley white pixels. In this way, the valley state of the image is detected, and 1) RGB white background detection compensates for difficult detection.

  << White Determination Unit 323c >> Here, the state variables MS and SS [I] used for white determination are updated. The contents are shown in the flowchart of FIG. Here, the state variable MS is addressed to the pixel of the processing target line (target line), and the state variable SS [I] is addressed to the pixel one line before the processing target line (processed line). This is 4-bit white background information representing the degree of white, and is generated by the processing shown in the flowchart of FIG. The maximum value represented by the state variables MS and SS [I] is set to 15, which means the whitest degree, and the minimum value is 0. That is, the state variables MS and SS [I] are data indicating the degree of white, and the larger the value represented, the stronger the white. At the start of the copying operation, the state variables MS and SS [I] are both initialized to 0.

  In the process of FIG. 5, first, the state variable of the target pixel to be processed one line before, that is, the white background information SS [I] and the pixel of the previous pixel on the same line as the target pixel (previous pixel: processed pixel). The state variable, that is, the white background information MS is compared (step S1). If the white background information SS [I] one line before is larger, it is used as the temporary white background information MS of the target pixel (step S2). Otherwise, the state variable MS of the preceding pixel is set as the temporary white background information MS of the target pixel. This means that information closer to white of the white background information of the peripheral pixels is selected.

  After the copying operation is started, when 1) a white area, that is, a white background is detected by RGB white background detection [1] White background determination signal = “1”, which is an output of RGB white background detection, a pixel one line before the target pixel The white background information SS [I] is updated to 15 (steps S3 and S4), and the white background information MS of the target pixel is also set to 15 (step S5). The white background information MS of the target pixel is written into the main scanning position (F) of the target pixel in the line memory for the current line (target line) of the line memory LMP shown in FIG. SS [I] is written in the main scanning position (F) of the target pixel of the line memory for the previous one line of the line memory LMP shown in FIG. 12 (steps S3, 4, 5). Next, the white background information SS [I] addressed to the previous pixel is propagated to the previous pixel as follows (steps S14 to S17). [I] means the main scanning position of the target pixel, and [I-1] means the position of the pixel one pixel before (in the main scanning direction x) (the pixel immediately before the target pixel).

SS [I-1] <SS [I] -1
time,
SS [I-1] = SS [I] -1
Is set in the line memory (steps S14 and S15). That is, in the line one line before the target pixel, the white background at the position (F) of the target pixel from the white background information SS [I-1] one pixel before (E) from the position (F) of the target pixel in the main scanning direction. If the value “SS [I] −1” obtained by subtracting 1 from the information SS [I] is larger (whiteness is stronger), the pixel one pixel before the position (F) of the target pixel on the line one line before The white background information SS [I-1] addressed to (E) is updated to a value obtained by lowering the white intensity by 1 from the white background information SS [I] at the position (F) of the target pixel.

next,
SS [I-2] <SS [I] -2
time,
SS [I-2] = SS [I] -2
Is set in the line memory (steps S16, 17-14, 15);
next,
SS [I-3] <SS [I] -3
time,
SS [I-3] = SS [I] -3
Is set in the line memory (steps S16, 17-14, 15).

In the same manner, finally,
SS [I-15] <SS [I] -15
time,
SS [I-15] = SS [I] -15
Is set in the line memory (steps S16, 17-14, 15). The lower limit value MIN of the value of the white background information SS [I] is 0, and when it is less than 0, it is kept at 0. The same applies to step S13 described later.

  By the processing of these steps 14 to 17, the white background information SS one line before and before the main scanning position of the target pixel is changed to one for the positional deviation of one pixel in the main scanning direction x from the white background information MS of the target pixel. The value is updated to a value reduced by the reduction rate, and the white background information of the target pixel is propagated at the reduction rate in the main scanning direction x one line before the main scanning (white propagation processing). However, this is a case where the white background information one line before is a smaller value. For example, if the pixel one line before is the above 1. ) When a white background (white area) is detected by RGB white background detection, the white background information is 15 and is the highest value, so rewriting is not performed.

  When the pixel of interest is updated and becomes a non-white background [1] White background determination signal = “0”, which is the output of RGB white background detection, the process proceeds from step S3 to step S6 and subsequent steps, and 2] Not a color gamut determination signal d = “1” which is an output of color gamut detection (a non-color gamut), binarized white [binary white determination signal which is an output of the binarization unit 323e] = “1”], and when the state variable of the pixel of interest temporarily determined in Steps 1 and 2, that is, the white background information MS is equal to or greater than a threshold thw 1 (for example, 13), the white background information MS addressed to the pixel of interest is incremented by one. (Steps S6 to 10). That is, the white level is updated to a strong value by 1. The maximum value max of the white background information MS is set to 15, and when it exceeds 15, it is limited to 15 (steps S9 and S10). Even when the route is advanced, the above-described steps S5 and 14 to 17 are executed. That is, white propagation processing is performed.

  When the target pixel is non-colored and binary white, but the white background information MS is less than thw1 (for example, 7), thw2 (for example, 1) or more, and is a valley white pixel, the state variable MS is set to the value as it is. Hold (steps S8, 11, 12). Even when the route is advanced, the above-described steps S5 and 14 to 17 are executed. That is, white propagation processing is performed.

  When none of the above conditions is met, that is, when the target pixel is a color background or non-binary white, the white background information MS of the target pixel is decremented by 1 (step S13). In other words, the white level information is updated to white background information weak by one. The minimum value MIN of the white background information MS is 0, and is kept at 0 when it is less than 0. Even when the route is advanced, the above-described steps S5 and 14 to 17 are executed. That is, white propagation processing is performed.

  By generating the white background information MS as described above, the white information can be propagated to the peripheral pixels via the state variable (white background information) MS on the line memory LMP. As described above, the white background information MS is generated in step S3-4 in FIG. 5 based on the RGB white background determination signal that represents a white background when the color data (all of the R, G, and B image data) is smaller than the threshold thwss = 40. Including generation of white background information MS corresponding to colors of -5-14 to 17 and when the edge emphasis output of density data (G image data) (output of the filter unit 321) is smaller than the threshold thwsb = 50, This includes the generation of white background information MS corresponding to the density of the system in steps S7 to 13-5-14 to 17 in FIG. 5 based on the white background and the binarized white determination signal.

  The white determination unit 323c first detects 1) RGB white background in the RGB white extraction unit 323b until a white area is detected, that is, 1) RGB white background detection generates a white background determination signal “1” and responds to this. The operation (execution of step S4) is not performed until the generation of the color-corresponding white background information MS (steps S3-4-5-14 to 17) is started. This is to prevent a region that cannot be determined as a white region from being erroneously determined as a white pixel (white block) in white pattern matching (to be described later) of the G image data after edge enhancement processing by the filter unit 321.

  When the edge emphasis filter unit 321 is applied to a light color ground character, the data around the character becomes a value (white) having a lower level than the original image data (color ground), so the data after the edge emphasis processing of the filter unit 321 is performed. When white pattern matching is performed, that is, when white area determination is performed based only on generation of density-corresponding white background information MS (steps S7-13-5-14-17), the character ground around the color ground is erroneously determined as white. Although it is easy, white for determining a white pixel (white block) to be described later in an area that can be determined as a white area by generating the white background information MS corresponding to the color (steps S3-4-5-14 to 17). If the white background information MS is set to the highest value so that pattern matching is applied and the white background is not white in step 3, the white background condition is checked in detail in step S6 and subsequent steps. Since the white background information MS, which is one parameter for determining whether to apply ching, is adjusted, white pixels (white blocks) are detected by white pattern matching (to be described later) of the G image data after edge enhancement processing by the filter unit 321. This prevents misjudgment.

  For example, when the possibility of a color pixel is high, the white background information MS is lowered (step S13), and when there is a suspicion of a color pixel, the white background information MS is held (no change) (steps S11 to 13). Pattern matching prevents erroneous determination as a white pixel (white block), and prevents data around the character from having a lower level (white) than the original image data (color background).

  When the character is dense, the white background information MS is updated and propagated by the above-described processing (steps S3 to 5, 6 to 10, and 14 to 17), so that the possibility that the dense character region is erroneously determined as a pattern is reduced. . In addition, among characters such as complicated characters (for example, “call”), there are cases where 1) white detection cannot be performed by RGB white background detection. In that case, 3) white is detected by valley white pixel detection, and white background is detected. Since the information MS is held by the route in which the YES output of step S12 goes straight to step S5 and remains in a white background tendency, the possibility that a complicated character is erroneously determined as a design is reduced.

  As described above, when the pixel of interest is a color pixel surrounded by a white background, the color gamut determination signal d = “1” (color gamut), which is the output of 2) color gamut detection, Even in a complicated area, a light color pixel can be detected as a color background, and a threshold thwc for determining whether the periphery of the target pixel is white is set low (thwc = 20), and the periphery of the light color pixel (target pixel) is Since it is possible to detect light color pixels as a color background by strictly checking whether the background is white, it is possible to further reduce the possibility that a complicated character is erroneously determined to be a design.

  As described above, since a light color pixel can be detected more precisely as a color background, when a color background is detected, the process proceeds from step S6 to step S13 in FIG. 5, and the state variable MS is lowered to determine the color background as white. In addition to being able to reduce the possibility, in addition to the threshold thwss (eg, 40) when generating the white background determination signal referred to in step S3, the threshold when generating the binary white determination signal referred to in step S7 If thwsb (for example, 50) is set to a large value and the color background is not determined (step S6: NO), the probability that the binarization unit 323e regards it as white is increased, and steps S7 to S10 in FIG. The state variable MS is increased to increase the possibility of determining a white area.

  That is, in the above-described 1) RGB white background detection, a strict white determination with a low threshold of thwss = 40 and a low probability of determining white is performed, and when it is determined that there is a white background, the state variable MS is performed by the processing from step S3 in FIG. To increase the possibility of judging the character background to be white. If the white background is not determined by the strict white determination, conversely, the strict color gamut determination with high reliability for detecting a thin color pixel as a color gamut as a color gamut, that is, 2) color gamut detection is performed. Refer to the result, and when it is not determined to be a color background, once again, a white determination with a threshold value thwsb = 50 that has a high probability of determining white, that is, refer to the binarization unit 323e. If the determination is white, the state variable MS is increased to increase the possibility that the character background is determined to be white (steps S7 to S10). Since there is this processing (steps S6 to S10), when the background density unevenness is thinner than the color background and the detected light color pixel, for example, when there is unevenness in the background of the document such as show-through, the fine background unevenness of the document. As a result, it is possible to prevent the state variable MS from significantly changing in binary, and to prevent the next white pattern matching unit 323d from determining whether or not the pixel is a white pixel in the scanning direction. As a result, when the background is a light color background, fine color loss (white background) does not appear in conjunction with the fine background unevenness of the document such as show-through.

<< White Pattern Matching Unit 323d >> It is determined whether the background is white based on whether or not there is a continuous white pixel in a 5 × 5 pixel unit block centered on the target pixel. Therefore, for the target pixel, when the following expression is satisfied, the target pixel is temporarily determined as a white pixel and white pattern matching is performed:
(Non-color pixel & (white background information MS ≧ thw1 (13)) & binarized white) #
(Non-color pixel & (white background information MS ≧ thw2 (1)) & valley white pixel & binarized white)
Here, the target pixel for checking whether or not this conditional expression is satisfied has been subjected to the white propagation process in steps S5 and 14 to 17 in FIG. “White background information MS” is the white background information MS [I] of the target pixel to be checked after the white propagation process. However, MS [I] is the white background information after the white propagation processing, and I is the position in the main scanning direction x of the target pixel to be checked, and the white determination unit 323c described above performs the state variable MS. This is different from the position in the main scanning direction x of the pixel of interest for which is calculated.

  In the conditional expression, “non-color pixel” indicates that the color gamut determination signal d, which is the output of 2) color gamut detection, is “0”, and “binary white” indicates that the binarization unit 323e The binarized white determination signal is “1” (binarized white), and “valley white pixel” means that the detection result of the above 3) valley white pixel detection is a valley white pixel. And # means logical OR (or :). The white pattern matching is to check whether the output (whether it is a white pixel) determined by the conditional expression corresponds to any one of the vertical and horizontal diagonal continuous patterns PMPa to PMPd in FIG. White circles attached to the patterns PMPa to PMPd mean white pixels. It does not matter whether the other blank pixels are white pixels.

  If the white pixel distribution of the 5 × 5 pixel matrix centered on the target pixel corresponds to the pattern PMPa, PMPb, PMPc, or PMPd in FIG. 12, it is determined that the target pixel is a white pattern pixel.

<Gray judgment>
<< Gray Pixel Detection >> Hue division of R, G, B, Y, M, C, and Bk is performed, and a pixel having a low density is detected for each hue. Hue division is the same as color determination described later. Here, the filtered G data is compared with thgr, and if it is larger than the G data or if it is a color pixel in RGB white extraction color pixel detection, the following calculation is performed. If the condition is satisfied, the pixel is a gray pixel. Here, the threshold is changed for each color because the maximum density of each ink is different.
4.1) RY hue region boundary (ry)
R-2 * G + B> 0
4.2) Y-G hue region boundary (yg)
11 * R-8 * G-3 * B> 0
4.3) GC hue region boundary (gc)
1 * R-5 * G + 4 * B <0
4.4) CB hue region boundary (cb)
8 * R-14 * G + 6 * B <0
4.5) BM hue region boundary (bm)
9 * R-2 * G-7 * B <0
4.6) MR hue region boundary (mr)
R + 5 * G-6 * B <0
4.8) Y pixel pixel determination (gry)
(It is a color pixel) & (ry == 1) &
(Yg == 0) & (maximum RGB value <thmaxy)
4.9) G pixel determination (grg)
(It is a color pixel) & (yg == 1) &
(Gc == 0) & (maximum RGB value <thmaxg)
4.10) C pixel determination (grc)
(It is a color pixel) & (gc == 1) &
(Cb == 0) & (maximum RGB value <thmaxc)
4.11) B pixel determination (grb)
(It is a color pixel) & (cb == 1) &
(Bm == 0) & (maximum RGB value <thmaxb)
4.12) M pixel determination (grm)
(It is a color pixel) & (bm == 1) &
(Mr == 0) & RGB maximum value <thmaxm)
4.13) R pixel determination (grr)
(It is a color pixel) & (mr == 1) &
(Ry == 0) & (maximum RGB value <thmaxr)
4.14) When not a color pixel (grbk)
(RGB maximum value <thmaxbk)
4.15) Gray pixel determination When satisfying any of the conditions 4.8) to 4.15), a gray pixel is determined. Note that “==” is a C language notation.

  This processing is performed by the gray pixel detection unit 323b-1 in FIG. As described above, the RGB white extraction unit 323b includes the gray pixel detection unit 323b-1, the color pixel detection unit 323b-2, and the RGB white background detection unit 323b-3, and R, G, and B image data are stored in these units. input. The output of the gray pixel detection unit 323b-1 is input to the gray pattern matching unit 323h, and the pattern matching result of the gray pattern matching is input to the gray expansion unit 323i. After performing expansion processing, the output is input to the determination unit 323m. In addition, the outputs of the color pixel detection unit 323b-2, the RGB white background detection unit 323b-3, and the binarization unit 323e are input to the white determination unit 323c, and the determination result of the white determination unit 323c is input to the white pattern matching unit 323d. The pattern matching result is input to the white pattern correction unit 323j and the white correction unit 323g. The correction result of the white pattern correction unit 323h is further processed by the white expansion unit 323k and the white contraction unit 323l and then input to the determination unit 323m, and the processing result of the white correction unit 323g is input to the determination unit 323m as it is. . It should be noted that the isolated points can be removed by performing a contraction process before the gray expansion unit 323i performs the expansion process. The white pattern matching unit 323d, the white pattern correction unit 323j, the white expansion unit 323k, the white contraction unit 323l, and the white correction unit 323g are configured to detect a boundary region that is not white and white, and are output from the white correction unit 323g. Indicates the line width, the output of the white contraction part 323l indicates a white region, and the output of the gray expansion part 323i indicates medium density. Therefore, the determination unit 323m makes a determination by assigning priorities to these three outputs, and outputs the determination result to the subsequent stage. In this case, priority 1 is line width information from the white correction unit 323g, priority 2 is medium density information from the gray expansion unit 323i, and priority 3 is white area information from the white contraction unit 323l. is there.

  << Gray Pattern Matching Unit 323h >> The gray pattern matching unit 323h performs the following pattern matching assuming that D is a gray pixel and bk is darker than the gray pixel. Since the copied original has a thin line pattern of 200 lines and a 300-line line, the following pattern is adopted so that the copied original is also detected in gray. A pixel that matches the following pattern is a gray pixel. FIGS. 22A and 22B show patterns at this time. FIG. 22A shows a pattern for 200 lines, and FIG. 22B shows a pattern for 300 lines.

(D15
D25
D35
D32 D45 D38
! BK41 D42! BK43! BK44 D55! BK46! BK47 D48! BK49
D52 D65 D58
D75
D85
D95)
# (D05
D15
D25
D31 D33 D35 D37 D38
D41! BK42 D43! BK44 D45! BK46 D47! BK48 D48
D51 D53 D55 D57 D58
D65
D75
D85)
<< White Pattern Correction Unit 323j >> The white pattern correction unit 323j is isolated by white pixel pattern matching (1 × 1, 1 × 2, 2 × 1, 2 × 2, 1 × 3, 3 × 1 white pixels). The active pixel that is present is deactivated. This removes isolated pixels.

  << White Expansion Unit 323k >> In the white expansion unit 323k, the result of white pixel pattern matching correction is ORed by 7 × 41.

  << White Contraction Unit 323l >> The white contraction unit 323l performs 1 × 33 AND of the result of white expansion in the white expansion unit 323k. By performing white expansion and white contraction, inactive pixels existing in a small area with expansion are removed from the correction result in the white pixel pattern matching unit 323d. The determination result includes a boundary area on the non-white background side with respect to the white background and the boundary portion. In other words, the area is larger than the white background.

  << White Correction Unit 323g >> In the white correction unit 323g, in the 15 × 11 pixel centered on the target pixel marked with “X” in the block pattern BCP in FIG. When a candidate block exists, white block correction data is given to the target block. As a result, a region surrounded by a white background is set as a white region.

<< Gray Expansion Unit 323i >> The gray expansion unit 323i performs 11 × 11 OR processing on the result of gray pattern matching. This makes the area slightly larger than the gray area.
This output result (gray determination result) is output to the determination 323m in FIG. 21 and the comprehensive determination 326 in FIG.

  Further, the gray expansion unit 32i performs the following processing in order to perform high density detection. High density detection consists of three blocks: high density detection, black expansion, and black contraction. First, the region of the high density portion of the image data is extracted. In high density detection, if the maximum value of RGB image data is larger than a predetermined threshold value thk, high density data is output. When the result of high density detection is high density data, 17 × 12 OR processing is performed as 1. Next, 9 × 4 AND processing is performed on the result of black expansion by black contraction. Due to black expansion and black contraction, the peripheral four-pixel region is expanded with respect to the result of high density detection. Here, the expansion of four pixels is considered to correct even if the peripheral pixels become thin due to the influence of flare or the like. The result after black expansion is output to the overall determination 326 in FIG. 4 as a high density detection result.

  << Determination Unit 323m >> In the determination unit 323m, the white background is set when the result of the white correction unit 323g is active, or when the result of the white contraction unit 323l is active and the result of the gray expansion unit 323i is inactive. It can be expressed as the following equation.

White correction result # (white shrinkage result &! Gray expansion result)
Here, in the result of white correction, the area surrounded by the white background is definitely determined as the white area, and the result of white shrinking &! As a result of the gray expansion, a dark black character periphery is set as a white area, and a low density area is set as a non-white area.

  In FIG. 13, in the black protrusions surrounded by the circles Bp1 to Bp4, one or more white candidate blocks exist in each of the 6 × 4 pixel regions at the four corners in 15 × 11 pixels centering on the above-described target block. At this time, the white block is replaced with the white block by white block correction giving white block correction data to the target block. Making a black region surrounded by a white background like the black protrusions surrounded by the circles Bp1 to Bp4 as a white region lowers the possibility of determining it as a picture portion. In the overall determination unit 326 described later, the non-white area is determined as a pattern, but the possibility of erroneously determining a black area surrounded by a white background as a black protrusion surrounded by the circles Bp1 to Bp4 is reduced. Furthermore, as a result of white shrinkage, the boundary between black and white is determined as a white area (character area) based on the result of gray expansion, so a dark character edge is determined as a white background regardless of the thickness of the character. It can be determined as an edge. A character edge is not determined in a portion having a low density.

<Adjustment of text / photo judgment level>
As described above, in the white region extraction unit 323, the white determination unit 323c uses the white background determination signal of the RGB white extraction unit 323b, the color background determination signal d and the valley white pixel determination signal, and the binarized white of the binarization unit 323e. White background information MS, which is a state variable representing the degree of white corresponding to the determination signal, is generated. The white pattern matching unit 323d temporarily determines whether the pixel of interest is a white pixel based on the color background determination signal d, the white background information MS, the binarized white determination signal, and the valley white pixel determination signal, and includes the pixel of interest. Whether the pixel is a white pixel is determined by white pixel distribution pattern matching with respect to the pixel matrix. Using this result and the results of the black determination unit and the black pattern matching unit 323f, the white correction unit 323g determines whether the pixel of interest is a boundary between a black background and a white background (white region: character region). Note that the white region extraction unit 323 has the circuit configuration of FIG. 21 in the case of gray pixel determination, but the black and white determination is processed by the circuit configuration of FIG.

  The white background determination signal (see step S3 in FIG. 5) of the RGB white extraction unit 323b is “1” (white background) when all of the R, G, and B image data of the target pixel are smaller than the threshold thwss = 40. Increasing this threshold thwss increases the probability of determining a large value of the white background information MS and increases the probability of extracting the “white area” (the boundary between the black background and the white background: the character area) (ie, extracting the pattern area). The probability of The reverse occurs when the threshold value thwss is decreased.

  The binarized white determination signal of the binarization unit 323e (see step S7 in FIG. 5) is “1” (binarization) if the edge enhancement output of the G image data of the filter unit 321 is smaller than the threshold thwsb = 50. White). Increasing this threshold thwsb increases the probability of determining a large value of the white background information MS and increases the probability of extracting the “white region” (that is, the probability of extracting the pattern region decreases). If the threshold value thwsb is reduced, the opposite is true.

  Since the image data for “white area” is subjected to image processing for clearly expressing the character image in a later step, when the threshold values thwss and thwsb are increased, image processing with high priority is performed on the characters. The image data in the non-white area, that is, the picture (picture) area, is subjected to image processing for faithfully representing the picture or picture in a later process. Therefore, if the threshold values thwss and thwsb are reduced, the priority is given to the picture (picture). High image processing is performed.

  By the way, if the color gamut determination signal d (refer to step S6 in FIG. 5) of the RGB white extraction unit 323b is “1” (color gamut), the white background information MS is lowered, and the probability of extracting the “white area” is high. It becomes low (that is, the probability of extracting the pattern area becomes high). 2) Process for generating a color gamut determination signal d by color gamut detection. , C.I. When the threshold thwc (for example, 20) used in the above is reduced, the probability that peripheral pixels (Δ and □ in FIG. 11) are simultaneously detected as color pixels, that is, the probability that (exclusive NOR of b and c) = “1” increases. The probability of obtaining the color background determination signal d = “1” (color background) increases, and the probability of extracting the “white area” decreases (that is, the probability of extracting the pattern area increases).

Therefore, in the present embodiment, in the operation / display unit OPB in FIG. 2, the menu display of the input mode by key input and the key image (parameter designation key and up / down key) on the menu screen displayed on the liquid crystal display are displayed. The thresholds thwss, thwsb, and thwc are adjusted as follows by adjusting the “character / photo level” in the parameter adjustment that is adjusted by the operation:
Parameter Text side adjustment value Standard Photo side adjustment value 6 5 4 3 2 1 0
thwss 46 44 42 40 38 36 34
thwsb 56 54 52 50 48 46 44
thwc 26 24 22 20 18 16 14
That is, the standard value (default) of the parameter “character / photo level” that is adjusted and set by the operator on the operation / display unit OPB is “3”, and this default value is the character / photo level and the threshold values thwss, thwsb, and 3 is written in the ROM 358 shown in FIG. 3 together with a conversion table representing the relationship with thwc. When the power is turned on to the IPU 300 shown in FIG. 3 and the CPU 357 initializes the IPU 300, the CPU 357 reads characters / photos from the ROM 358. The default value of the level is read, and the corresponding threshold values thwss, thwsb, and thwc are read from the conversion table, written in the registers addressed to the respective threshold values in the RAM 356, and used for the above-described processing in the white area extraction unit 323. Thereafter, when the character / photo level is adjusted by input from the operation board OPB, and the adjusted value A is given from the main controller 10 to the CPU 357, the CPU 357 sets the parameters thwss, thwsb and the adjusted value A. Each value of thwc is read from the conversion table of the ROM 358 and written to the parameter addressed to the RAM 356.

  When the threshold values are set to the standard values thwss = 40, thwsb = 50, and thws = 20, the operator uses the operation board OPB to increase the value of “character / photo level” by i (for example, 1) to “Up”. Then, the thresholds thwss, thwsb, and thwc are set to values that are changed in the character priority direction by 2i (2). Conversely, when the operator reduces the value of “character / photo level” by “down” by i (for example, 1), the threshold values thwss, thwsb, and thwc are set to values that are changed to the photo priority direction by 2i (2).

<Halftone extraction>
<< Halftone Extraction Unit 324 >> As shown in FIG. 23, the halftone dot extraction unit 324 includes a first halftone dot peak detection unit 324a, a second halftone dot peak detection unit 324b, a third halftone dot peak detection unit 324c, and a first halftone dot detection unit 324c. It comprises a dot area detector 324d, a third halftone dot area detector 324e, and temporary storage means (temporary memory) 324f. G image data is input to the first halftone peak detection unit 324a and the third halftone peak detection unit 324c, and B image data is input to the second halftone peak detection unit 324b. The first halftone dot region detector 324d receives the detection results of the first halftone dot peak detector 324a and the second halftone dot peak detector 324b, and the second halftone dot region detector 324e receives the third halftone dot region detector 324e. The detection result of the peak detector 324c is input. The temporary memory 324f temporarily stores the detection results of the first and second halftone dot area detection units 324d and 324f. Note that the halftone dot extraction unit 324 in FIG. 4 corresponds to N in FIG.

A first halftone dot peak detection unit 324a forms pixels of halftone dots (referred to as halftone dot peak pixels) from pixel density information in a two-dimensional local region having a predetermined size using G image data. Is a circuit for detecting When the following two conditions are simultaneously satisfied for the local region, the central pixel of the region is detected as a halftone dot pixel.
Condition 1: The density level of the central pixel is maximum (mountain peak) or minimum (valley peak) in the local region.
Condition 2: The absolute value of the difference between the average density level of the pixel pair and the density level of the center pixel is greater than or equal to the threshold Th for all pixel pairs that are in point symmetry with respect to the center pixel.

With reference to FIG. 14, the detection process of the 1st halftone peak detection part 324a is demonstrated concretely. In this example, a 5 × 5 pixel matrix (M × M pixel matrix when generalized) mask is used as the local region. If the sign of each pixel of the 5 × 5 pixel matrix is as shown in the pattern MPp of FIG. 11, the density Lc of the center pixel c3 serving as the target pixel is the maximum or minimum compared to the densities L1 to L8 of the surrounding pixels. And
abs (2Lc-L1-L8) ≧ Lth
And abs (2Lc-L2-L7) ≧ Lth
And abs (2Lc-L3-L6) ≧ Lth
And abs (2Lc-L4-L5) ≧ Lth
At this time, the center pixel (Lc) of the mask is detected as a halftone dot peak pixel. The abs function means taking an absolute value. Lth is a threshold value (fixed value).

  Specifically, the surrounding pixels are pixels with a surrounding pixel distribution pattern MPa or MPb quadrangle shown in FIG. When either halftone dot pixel detection described above based on the surrounding pixel distribution patterns MPa and MPb detects a halftone peak pixel, a detection signal representing a halftone dot pixel at the current pixel of interest (center pixel c3) give. The reason for using the two patterns is to deal with a wide range of halftone dot lines.

  The pattern MPa is defined as L1 = b2, L2 = b3, L3 = b4, L4 = c2, L5 = c4, L6 = d2, L7 = d3, L8 = d4. Here, L1 = b2 means that the density of the pixel b2 is set to the value of L1 in the above-described halftone peak pixel detection calculation.

  The pattern MPb is defined as L1 = b2, L2 = a3, L3 = b4, L4 = c1, L5 = c5, L6 = d2, L7 = e3, L8 = d4.

  In the case of copying, enlargement / reduction in the sub-scanning direction y is performed at low and high document scanning speeds of the scanner 200. Therefore, the scanner 200 provides image data with enlargement / reduction in the sub-scanning direction y. . Therefore, at the time of reduction, the patterns MPc and MPd shown in FIG. 14 are used instead of the aforementioned patterns MPa and MPb. When enlarging, the patterns MPe and MPf shown in FIG. 14 are used. In addition, in the patterns MPe and MPf, a pixel given a triangle mark may be added to the above-mentioned “surrounding pixels”.

  The second halftone peak detector 324b detects halftone dots using B data, and has the same function as the first halftone peak detector 324a. Since the first halftone peak detection unit 324a uses G image data, it reacts to most colors, but does not react to Y, so the second halftone peak detection unit 324c uses B image data. This is an auxiliary purpose for detecting the halftone dot peak of Y.

  The halftone dot area detection 324c is a two-dimensional small area having a predetermined size for halftone dot peak pixels detected by either the first halftone dot peak pixel detection 324a or the second halftone peak pixel detection 324b. Counting is performed every time, and the sum of the halftone dot peak pixels of the peaks and valleys is taken as the count value P of the small area. When the count value P is larger than the threshold value Pth, all the pixels in the small area (or in the case of pixel unit processing, only the central pixel of the small area) are determined as halftone dot areas. The result of the determination is stored in the temporary memory 324f.

With reference to Fig.24 (a), the detection process of the 3rd halftone peak detection part 324c is demonstrated concretely. The detection process of the third halftone dot peak detection unit 324c is intended to detect 100 lines or less and 65 lines (newspaper halftone dots) or more, and a 7 × 7 pixel matrix (M × M when generalized) is used as a local region. This is an example employing a pixel matrix mask. As shown in the pattern of FIG. 24C, the density Lc of the central pixel group serving as the target pixel is maximum or minimum as compared with the density groups L1 to L8 of the surrounding pixels.
abs (2Lc-L1-L8) ≧ Lth
And abs (2Lc-L2-L7) ≧ Lth
And abs (2Lc-L3-L6) ≧ Lth
And abs (2Lc-L4-L5) ≧ Lth
At this time, the center pixel (Lc) of the mask is detected as a halftone dot peak pixel. The abs function means taking an absolute value. Lth is a threshold value (fixed value).

  Specifically, the surrounding pixels are pixels having a surrounding pixel distribution pattern shown in FIG. When one of the first and second halftone peak detection units 324a and 324b based on the surrounding pixel distribution pattern detects a halftone peak pixel, a halftone dot pixel is used as the target pixel (center pixel d4) at that time. A detection signal representing is given. The reason why the two patterns are used is to deal with a wide range of halftone dot area ratios.

The density of Lc is obtained as follows with reference to surrounding pixels.
Lc = Min (d4, d3, d5, c4, e4)
When this Lc is the maximum value for the surrounding pixels, the pattern is
L1 = Max (a1, a2, b1)
L2 = Max (a3, a4, a5)
L3 = Max (a6, a7, c7)
L4 = Max (c1, d1, e1)
L5 = Max (c7, d7, e7)
L6 = Max (f1, g1, g2)
L7 = Max (g3, g4, g5)
L8 = Max (g6, g7, f7)
It is determined. Here, L1 = Max (a1, a2, b1) means that the maximum value of the density of the pixels a1, a2, b1 is set as the value of L1 in the above-described halftone peak pixel detection calculation.
Lc = Min (d4, d3, d5, c4, e4) means that Lc is the smallest of d4, d3, d5, c4, and e4.

Lc = Max (d4, d3, d5, c4, e4)
When this Lc is the minimum value for the surrounding pixels, the pattern is
L1 = Min (a1, a2, b1)
L2 = Min (a3, a4, a5)
L3 = Max (a6, a7, c7)
L4 = Max (c1, d1, e1)
L5 = Max (c7, d7, e7)
L6 = Max (f1, g1, g2)
L7 = Max (g3, g4, g5)
L8 = Max (g6, g7, f7)
It is determined.

  In the case of copying, enlargement / reduction in the sub-scanning direction y is performed at low and high document scanning speeds of the scanner 200. Therefore, the scanner 200 provides image data with enlargement / reduction in the sub-scanning direction y. . Therefore, at the time of reduction, the pattern shown in FIG. 14B is used. When enlarging, the pattern shown in FIG. 14A is used.

  The calculation formula of the third halftone peak detection unit 324c refers to the target pixel with a plurality of pixels (calculations of min and max), not with data of one pixel. This is because halftone dots with a low number of lines have a large grayscale period, so if one pixel is determined, the influence of noise (dust) is reduced by referring to surrounding pixels, and the amount of arithmetic operations is reduced. Since the arithmetic expression can be used in common with other blocks, hardware is easy.

  The first halftone dot region detection unit 324d counts the peak and valley halftone dot pixels detected by the first halftone dot peak detection unit 324a for each two-dimensional small region having a predetermined size. Is the count value P of the small area. When the count value P is larger than the threshold value Pth, all the pixels in the small area (or in the case of pixel unit processing, only the central pixel of the small area) are determined as halftone dot areas. The result of the determination is stored in the temporary memory 324f.

  If either the first halftone dot region detection unit 324d or the second halftone dot region detection unit 324e is a halftone dot region, the halftone dot / non-halftone dot determination result of the processed region near the small region of interest (peripheral The threshold value Pth is adaptively changed according to the feature information). In the present embodiment, two values TH1 and TH2 (where TH1> TH2) are prepared as the threshold value Pth, and one of the values is determined based on the determination result of the processed region in the vicinity of the target small region stored in the temporary memory 324f. Select a value. That is, if the neighboring area is determined to be a non-halftone dot area, there is a high possibility that the area is a line drawing area. Therefore, TH1 whose conditions are severer is selected as the threshold value Pth in order to reduce false detection. On the other hand, if it is determined that the neighboring region is a halftone dot region, since there is a high possibility that it is a halftone dot region, TH2 where the condition is relaxed is used as the threshold value Pth. Note that TH1 is selected as the initial value of the threshold value Pth.

  The AMP on FIG. 14 shows the distribution of the small regions described above. Each of S1 to S4 of the small area distribution pattern AMP is, for example, a small area (block) having a size of 4 × 4 pixels. S4 is a small area of interest, and S1, S2, and S3 are processed small areas. Suppose that When it is determined that all of S1, S2, and S3 are halftone areas, Th2 is used as the threshold value Pth for the determination of S4. When one of S1, S2 and S3 is determined to be a non-halftone area, TH1 is selected as the threshold value Pth. A halftone dot region detection signal ht is output from the halftone dot extraction unit 324 when it is determined as a halftone dot region and is “1” when it is determined as a non-halftone dot region. However, this is only an example, and TH2 is selected when any one of S1, S2, and S3 is determined to be a halftone dot region, and TH1 is selected only when all are determined to be non-halftone regions. May be selected. Furthermore, the neighborhood area to be referred to may be only S1 or only S2.

  << Color Judgment Unit 325 >> When detecting color (chromatic) pixels and black (achromatic) pixels in a document, relative reading shifts of R, G, and B may cause sampling of each color image data or mechanical Exists for accuracy. This will be described with reference to FIG. FIG. 15A shows an image density signal. The black density signal is ideally black when the levels of the R, B, and G density signals coincide with each other. However, the actual image data is obtained by forming an image on the CCD 207 with the lens 206 and digitizing the image signal of the CCD 207. FIG. 15B shows an ideal high and low waveform. However, since a general scanner uses a three-line CCD sensor, the R, G, B line sensors are not read simultaneously in time, but the R, G, B line sensors are equal. Since they are arranged at intervals and cannot be read simultaneously in time, the reading position will inevitably shift. For example, the R, G, B color density signals representing the level-change black shown in FIG. 15B are relatively shifted as shown in FIG. If this shift is large, a color shift appears at the periphery of the black area.

  << Hue Division Unit 325a >> The color determination unit 325 finds a chromatic color region. The input data R, G, B is converted into signals of c, m, y and color determination w (white) by the hue dividing unit 25a. As an example of hue division, each color boundary is obtained, and the difference between the maximum value and the minimum value of R, G, and B image data in one pixel is defined as an RGB difference, and the following is performed. Here, the R, G, B image data becomes black (darkens) as the number increases.

1) RY hue area boundary (ry)
R-2 * G + B> 0
2) YG hue region boundary (yg)
11 * R-8 * G-3 * B> 0
3) GC hue region boundary (gc)
1 * R-5 * G + 4 * B <0
4) CB hue region boundary (cb)
8 * R-14 * G + 6 * B <0
5) BM hue region boundary (bm)
9 * R-2 * G-7 * B <0
6) MR hue region boundary (mr)
R + 5 * G-6 * B <0
7) Color determination w (white) pixel determination: If (R <thwa) & (G <thwa) & (B <thwa), y = m = c = 0. thwa is a threshold value.

8) Y pixel determination: If (ry == 1) & (yg == 0) & (RGB difference> thy), then y = 1 and m = c = 0. thy is a threshold value.

9) G pixel determination: If (yg == 1) & (gc == 0) & (RGB difference> thg), c = y = 1 and m = 0. thg is a threshold value.

10) C pixel determination: If (gc == 1) & (cb == 0) & (RGB difference> thc), c = 1 and m = y = 0. thc is a threshold value.

11) B pixel determination: If (cb == 1) & (bm == 0) & (RGB difference> thb), m = c = 1 and y = 0. thb is a threshold value.

12) M pixel determination: If (bm == 1) & (mr == 0) & (RGB difference> thm), m = 1 and y = c = 0. thm is a threshold value.

13) R pixel determination: If (mr == 1) & (ry == 0) & (RGB difference> thr), y = m = 1 and c = 0. thr is a threshold value.

14) BK pixel determination: When not corresponding to 7) to 13), y = m = c = 1.

Further, the color determination w pixel is determined. condition is,
(R <thw) & (G <thw) & (B <thw)
Then, it is set as a w pixel for a color pixel and is output as w. thw is a threshold value. Here, the priority of 7) to 14) is given priority to the smaller number. The above-described threshold values thwa, thy, thm, thc, thr, thg, thb are threshold values determined before copying (processing). The relationship between thw and thwa is thw> tha. The output signal is 3 bits of data of 1 bit for each of c, m, and y, and 1 bit of w for color pixel detection for color determination. Here, the threshold is changed for each hue because the threshold corresponding to the hue area is determined for each hue area when the chromatic range is different. This hue division is an example, and any formula may be used.

  Output lines c, m, y, and w of the hue division unit 325a are stored in five lines in the line memories 325b to 325e and input to the color pixel determination unit 325f.

  << Color Pixel Determination Unit 325f >> FIG. 6 shows the contents of the color pixel determination unit 325f. The data of c, m, y, and w for five lines are input to the pattern matching units 325f5 to 325f7 and the count units 325f1 to 325f4. First, the pattern matching unit 325f6 in the flow for obtaining the B / C signal will be described.

<< Pattern Matching Unit 325f6 >> When there is a w pixel for a color pixel, the pixel is corrected to c = m = y = 0. This correction increases the white level of the 5 × 5 pixel matrix centered on the pixel of interest. Next, the pixel of interest is a pixel other than all of c, m, y determined by the hue dividing unit 325a being 1 (c = m = y = 1) or all being 0 (c = m = y = 0) ( It is determined by checking whether the 5 × 5 pixel matrix matches the next pattern.
1) Color pixel pattern group 1-1) Pattern 1-1 (pm1)
D23 & D33 & D43
1-2) Pattern 1-2 (pm2)
D32 & D33 & D34
1-3) Pattern 1-3 (pm3)
D22 & D33 & D44
1-4) Pattern 1-4 (pm4)
D24 & D33 & D42
The central pixel (target pixel) is D33. FIG. 16 shows these patterns pm1 to pm4. White circles on these patterns indicate that at least one of c, m, and y is 1. Pattern matching is used to prevent picking up isolated points. On the other hand, when detecting a small area color such as a halftone dot, the central pixel is a pixel (color pixel) other than 1 (c = m = y = 1) or all 0 (c = m = y = 0). It may be determined whether or not.

2) Color thin line pattern group A color line surrounded by white is detected. The pattern used for this is shown in FIG. In FIG. 17, pixels with white circles are pixels in which c, m, and y are all 0. When the distribution of the data (c, m, y) of the 5 × 5 pixel matrix centered on the target pixel (center pixel) matches any of the patterns pw11a to pw14d in FIG. 17, the target pixel (center pixel) at that time ) Is regarded as a color line pixel.
2-1) Pattern 2-1 (pw11a to pw11d)
((D12 & D13 & D14) & (D42 & D43 & D44)) #
((D12 & D13 & D14) & (D52 & D53 & D54)) #
((D22 & D23 & D42) & (D42 & D43 & D44)) #
((D22 & D23 & D42) & (D52 & D53 & D54))
2-2) Pattern 2-2 (pw12a to pw12d)
((D21 & D31 & D41) & (D24 & D34 & D44)) #
((D21 & D31 & D41) & (D25 & D35 & D45)) #
((D22 & D23 & D24) & (D24 & D34 & D44)) #
((D22 & D23 & D24) & (D25 & D35 & D45))
2-3) Pattern 2-3 (pw13a to pw13d)
((D11 & D21 & D12) & (D35 & D44 & D53)) #
((D11 & D21 & D12) & (D45 & D44 & D55)) #
((D13 & D22 & D31) & (D35 & D44 & D53)) #
((D13 & D22 & D31) & (D45 & D44 & D55))
2-4) Pattern 2-4 (pw14a to pw14d)
((D13 & D24 & D35) & (D41 & D51 & D52)) #
((D14 & D15 & D25) & (D41 & D51 & D52)) #
((D13 & D24 & D35) & (D31 & D42 & D53)) #
((D14 & D15 & D25) & (D31 & D42 & D53))
3) White region pattern group Pattern matching is performed where c, m, and y are all zero. The pattern used for this is shown in FIG. In FIG. 18, pixels with white circles are pixels in which c, m, and y are all 0. When the distribution of the data (c, m, y) of the 5 × 5 pixel matrix centered on the target pixel (center pixel) matches any of the patterns pw21a to pw24d in FIG. 18, the target pixel (center pixel) at that time ) Is regarded as a white area pixel.
3-1) Pattern 3-1 (pw21a to pw21d)
(D21 & D31 & D41) #
(D22 & D32 & D42) #
(D24 & D34 & D44) #
(D25 & D35 & D45)
3-2) Pattern 3-2 (pw22a to pw22d)
(D12 & D13 & D14) #
(D22 & D23 & D24) #
(D42 & D43 & D44) #
(D52 & D53 & D54)
3-3) Pattern 3-3 (pw23a to pw23d)
(D52 & D51 & D41) #
(D53 & D42 & D31) #
(D35 & D24 & D13) #
(D25 & D15 & D14)
3-4) Pattern 3-4 (pw24a to pw24d)
(D54 & D55 & D45) #
(D53 & D44 & D35) #
(D31 & D22 & D13) #
(D21 & D11 & D12)
4) Determination of color pixel candidate 2 If the pattern matching result extracted above matches the following pattern, the pixel of interest is set as color pixel candidate 2 for color determination:
((Pm1 == 1) &
((Pw11 == 1) # (pw21! = 1))) #
((Pm2 == 1) &
((Pw12 == 1) # (pw22! = 1))) #
((Pm3 == 1) &
((Pw13 == 1) # (pw23! = 1))) #
((Pm4 == 1) &
((Pw14 == 1) # (pw24! = 1)))
Here, (pm1 == 1) means that the data distribution centered on the target pixel matches the pattern pm1, and (pw11 == 1) means that it matches any of the patterns pw11a to pw11d. This means that (pw21! = 1) matches with any of the patterns pw21a to pw21d. & Means logical product, and # means logical sum. With this pattern matching, a color pixel surrounded by a white area is set as a color pixel candidate, and when there is a white area other than that, it is not set as a color pixel. Those matched by color pixel pattern matching without a white area are color pixel candidates.

  << Counting unit 325f1 >> When a w determination pixel for color determination exists in a 5 × 5 pixel matrix centered on the target pixel, the c, m, y data determined by the hue division unit 325a of the pixel is c = m = Y = 0. This correction increases the white level of the pixel matrix. Then, the number of 1 of c, m, and y (c = 1, m = 1, y = 1) of each pixel in the pixel matrix is counted. If the difference between the maximum value and the minimum value of the count values for c, m, and y is greater than or equal to thcnt and the minimum value is less than thmin, color pixel candidate 1 is determined. thcnt and thmin are threshold values set before copying (processing). The plane is expanded to y, m, and c, the number is counted for each plane in the N × N matrix, and the minimum value is assumed to be black. This makes it possible to correct even if black pixel reading fails. A chromatic pixel is determined based on the difference between the maximum value and the minimum value. This corrects a pixel from which a black pixel is not read, and extracts a chromatic pixel. If there is a chromatic pixel of a certain pixel in a 5 × 5 pixel matrix centered on the pixel of interest, the pixel of interest is a chromatic pixel.

  << Color Pixel Determination Unit 325f8 >> Based on the outputs of the pattern matching unit 325f6 and the count unit 325f1, the color pixel determination unit 325f8 determines whether the pixel is a color pixel. If the color pixel candidate 1 and the color pixel candidate 2, the color pixel 1 is assumed.

  << Blocking Unit 325f9 >> The output of the color pixel determining unit 325f8 is blocked by the blocking unit 325f9. Blocking means that if there is one or more color pixels 1 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as one color pixel block. In the processing after the block forming unit 325f9, 4 × 4 pixels are regarded as one block and output in block units.

  << Isolated Point Removing Unit 325f10 >> The block data is removed by the isolated point removing unit 325f10 as an isolated point if there is no color pixel block in the adjacent block of the target block.

  << Expansion Unit 325f11 >> The output of the isolated point removal unit 325f10 is expanded to 5 × 5 blocks in the expansion unit 325f11 when there is one color pixel block. The reason for the expansion is to prevent black character processing around the color pixel. Here, the output B / C signal outputs L (chromatic) when the color pixel is one block, and outputs H (achromatic) at other times.

  << Counting unit 325f2 >> When there is a w determination pixel for color determination in a 5 × 5 pixel matrix centered on the pixel of interest, the c, m, y data determined by the hue division unit 325a of the pixel is c = m = Correct to y = 0. This correction increases the white level of the pixel matrix. Then, the number of c, m, and y of 1 (c = 1, m = 1, y = 1) of each pixel in the pixel matrix is counted. If the difference between the maximum value and the minimum value of the count values for c, m, and y is greater than or equal to thacnt and the minimum value is less than thatmin, the pixel of interest is set as a color pixel candidate 1. “thacnt” and “thamin” are threshold values set before copying (processing).

  << Color Pixel Determination Unit 325f12 >> Based on the outputs of the pattern matching unit 325f6 and the count unit 325f2, the color pixel determination unit 325f12 determines whether the pixel is a color pixel. If it is the color pixel candidate 1 and the color pixel candidate 2, it is set as the color pixel 2.

  << Blocking Unit 325f13 >> The output of the color pixel determining unit 325f12 is blocked by the blocking unit 325f13. That is, if there is one or more color pixels 2 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a color pixel 2 block. In the processing after the block forming unit 325f13, 4 × 4 pixels are set as one block and output in block units.

  << Density section 325f14 >> If there are 3 or more active conditions (color pixel 2 blocks) in the 3 × 3 block and the target block is active (color pixel) to remove the isolated block, the target block becomes the active block (Color pixel 2 block).

  << Counter 325f3 >> The number of c, m, and y 1 (c = 1, m = 1, y = 1) of each pixel in the 5 × 5 pixel matrix centered on the target pixel is counted. If the difference between the maximum value and the minimum value of c, m, and y for each of c, m, and y is equal to or greater than tha1cnt, and the counted minimum value of c, m, and y is less than tha1min, color pixel candidate 3 is determined. tha1cnt and tha1min are threshold values set before copying (processing).

  << Pattern Matching Unit 325f5 >> It is determined by pattern matching using a 5 × 5 pixel matrix whether the pixel (c, m, y) determined by the color pixel detection is a color pixel. The pattern is the same as that of the pattern matching unit 325f6. The pixel matched by pattern matching is set as a color pixel candidate 4.

  << Color Pixel Determination Unit 325f15 >> If the color pixel candidate 3 is the color pixel candidate 4, the color pixel 3 is determined.

  << Blocking Unit 325f16 >> The output of the color pixel determining unit 325f15 is blocked by the blocking unit 325f16. That is, if there is one or more color pixels 3 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a color pixel 3 block. The processing after the block forming unit 325f16 outputs 4 × 4 as one block.

  << Density 325f17 >> If there are three or more active conditions (color pixel 3 blocks) in the 3 × 3 block and the target block is active (color pixel 3) in order to remove the isolated block, the target block is activated. Let it be a block (3 blocks of color pixels).

  << Counting unit 325f4 >> 1 of c, m, and y (c = 1, m = 1, y = 1) determined by the hue dividing unit 325a of each pixel in the 5 × 5 pixel matrix centered on the target pixel Count the number. If the minimum value of the count values of c, m, and y is greater than or equal to thabk, the pixel of interest is set as a black pixel candidate 1. thabk is a threshold value set before copying (processing).

<< Pattern Matching Unit 325f7 >> In a 5 × 5 pixel matrix centered on the pixel of interest, pattern matching is performed on a pixel with c = m = y = 1.
1-1) Pattern 1-1 (pm1)
D23 & D33 & D43
1-2) Pattern 1-2 (pm2)
D32 & D33 & d34
1-3) Pattern 1-3 (pm3)
D22 & D33 & D44
1-4) Pattern 1-4 (pm4)
D42 & D33 & D24
These patterns are shown in FIG. 16, and the pixels with circles in the figure are pixels with c = m = y = 1. When matching with any of these patterns, the target pixel is set as a black pixel candidate 2.

  << Achromatic determination unit 325f18 >> If the target pixel is the black pixel candidate 1 and the black pixel candidate 2, the pixel is determined to be a black pixel.

  << Blocking Unit 325f19 >> The black pixel output is blocked by the blocking unit 325f19. In this block formation, if there is one or more black pixels in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a black pixel block. The processing after the block forming unit 325f19 outputs 4 × 4 pixels as one block and outputs in blocks.

  << Expansion unit 325f20 >> If a target block is active (black pixel block) and its surrounding pixels are non-active (non-black pixel) in a 3 × 3 block matrix, the target block is non-active (non-black pixel block) To.

  << Total Color Pixel Determination Unit 325f21 >> If the target block is determined to be active (color pixel 2) by the color pixel determination unit 325f12 and not determined to be active (black pixel) by the achromatic determination unit 325f18, the target block is colored (Color block) is determined. Also, when the color pixel determination unit 325f15 is active (color pixel), the color is determined.

  << Expansion unit 325f22 >> In order for the overall color pixel determination unit 325f21 to consider small characters as continuous with respect to the block determined to be a color, there is even one active block in the 9 × 9 block matrix centered on the target block. If there is, the target block is set as an active block. Here, the reason for the large expansion is to fill the gap between the characters.

  << Continuous Count Unit 325f23 >> The continuous count unit 325f23 determines whether the color document is a color document or a monochrome document by looking at the continuity of the color pixel blocks. By counting the number of continuous color pixels in the output data (color pixel block) of the expansion unit 325f22, it is determined whether the document is a color document.

  FIG. 7 shows the contents of this determination process. When the target pixel is in the color pixel block, the number of continuous color pixels of the target pixel is calculated with reference to the number of continuous color pixels of the upper left, upper, upper right, and left pixels of the target pixel (steps S21 to S26). Here, if the target pixel is, for example, the c3 pixel of the 5 × 5 pixel distribution pattern MPp in FIG. 11, the upper left, upper, upper right, and left pixels are the pixels b2, b3, b4, and c2, respectively. When the pixel of interest is not in the color pixel block, a continuous color pixel number of 0 is given to it (steps S21 to S27).

  When the target pixel is in the color pixel block, first, the number of continuous color pixels of the upper pixel (b3) of the target pixel (c3) is checked (step S22). A value obtained by adding 1 to the number of continuous color pixels of (b4) is given (step S24), and the number of continuous color pixels of the upper right pixel (b4) is added to the reference value A when the number of continuous color pixels of the upper pixel (b3) is 0. (Step S23). Next, a value obtained by adding 1 to the number of continuous color pixels of the upper left pixel (b2) is given to the reference value B, and a value obtained by adding 1 to the number of continuous color pixels of the upper pixel (b3) is given to the reference value B. Further, a value obtained by adding 1 to the number of continuous color pixels of the left pixel (c2) is given to the reference value D (step S25). Then, the highest value among the reference values A, B, C, and D is set as the number of consecutive color pixels of the target pixel (c3) (step S26).

  When the number of continuous color pixels is given to the target pixel (c3) as described above, it is checked whether the number of continuous color pixels is equal to or greater than the set value THACS (step S28). Is determined (step S29), and the processing of the continuous count unit 325f23 is ended there. If the number of continuous color pixels is less than the set value THACS, the target pixel is updated to the next pixel in the scanning directions x and y, and the above-described processing is repeated. As a result of performing the above-described processing on the entire surface of the document, if the number of continuous color pixels is less than the set value THACS until the end (steps S30 to S34), it is determined that the document is a monochrome image.

  The number of continuous color pixels is substantially the sum of vertical colored line segments and horizontal colored line segments. The number of consecutive color pixels in the upper right is different from others because it prevents double counting. Specific data on the number of continuous color pixels is shown in FIG. A small square including a number shown in FIG. 19 is a color pixel, and the number is a continuous number of color pixels given to the pixel. A block consisting of a series of small squares with numbers is a color pixel group, and even if one continuous color pixel in any color pixel group on the same document exceeds the set value THACS, it is a color document. The determination of color or black and white is confirmed (steps S28 and 29).

  The reason why it is divided from the color pixel determination units 1 to 3 (325f8 to 325f15) is to increase the accuracy of determining whether a color document or a monochrome document. The color pixel determination for black character processing is local and not so noticeable even if an erroneous determination is made. However, the determination of whether the original is a color original or a monochrome original affects the entire original if an erroneous determination is made. Therefore, the counting units 325f1-f4 are independent. Originally, it is better to make the hue dividing unit 325a independent. However, making the hue dividing unit 325a independent is not preferable because the memory of the pattern matching units 325f5-f7 increases. The increase in the amount of memory is reduced by changing the color pixel parameter (color pixel 1-3) with the parameters (color pixel candidate 1, 3 and black pixel candidate 1) of the count unit 325f1-f4. . The color pixel determination units 2 and 3 (325f12 and 325f15) are provided to detect a low density color such as yellow of a fluorescent pen, and further include an achromatic determination (black pixel determination) unit 325f18. This is because correction is made in the case of erroneous detection if the density is lowered. Light colors such as highlighters can be corrected with black data to a certain extent without any problem. When extracting multiple color pixels, only the level of w (white) is changed, so there is no need to have two memories for color pixel detection, and a capacity of one + 1 line is possible. is there.

  Since the count value is counted by the continuous count unit 325f23 by referring to the count data of the previous line and the count data of the current line, it is possible to accurately count the continuity of the peripheral pixels. It is possible to count continuations. In this embodiment, the hue determination is performed on the R, G, B image data. However, the hue determination is not limited to the R, G, B image data, and the hue determination is performed on a luminance color difference (for example, Lab). It is easy.

  << Overall Determination Unit 326 >> The overall determination unit 326 includes a character determination unit, an expansion processing unit, a character determination unit, and a decoding unit.

  << Expansion Processing Unit >> The expansion processing unit performs OR processing of 8 × 8 blocks on the result of the character determination unit, and then performs AND processing of 3 × 3 blocks to perform 4-block expansion processing. That is, if any block of the 8 × 8 block centered on the target block is a character edge, it is assumed that the target block is also a character edge block, and all 3 × 3 blocks centered on the target block are If it is a character edge, the block of interest is determined as the character edge, and the block of interest and three blocks adjacent to it are regarded as a character edge. The reason for performing the AND process after the OR process is that, particularly in the case of a black character, if there is a small non-black character area around the black character area, a sense of incongruity may be felt due to a difference in processing, for example, black appears to be faint It is. In order to prevent this, the non-black character area is enlarged by OR processing. The AND process is performed to obtain a desired expansion amount.

  << Character determination unit >> In the character determination unit, when the result of the edge extraction unit 322 is an edge, the result of the halftone extraction unit 324 is no halftone, and the white region result of the white region extraction unit 323 is a white region, Judged as a character edge. Otherwise, it is determined as a non-character edge (whether a pattern or a character), and the result is output to the expansion processing unit as shown in FIG.

  By the way, since a color copying machine scans four times to make one copy, the character determination result slightly differs for each scan. In particular, if non-black character determination is performed at the time of black image formation and black character determination is performed at times other than black image formation, this black character area becomes thin. Therefore, the expansion processing unit performs OR processing of 8 × 8 blocks at bk. Then, 3 × 3 block AND processing is performed, and when image formation other than bk is performed, 5 × 5 block OR processing is performed, and thereafter 1 × 1 block AND processing is performed. Note that performing 1 × 1 AND processing is synonymous with performing no processing because the result is the same as before processing. The result of the expansion process is output to the decoding unit as a character edge signal.

  By performing the expansion process in this way, the separation result is different and the character area is not thinned. This expansion process may darken the middle part of the character, but if the character is light relative to the edge of the character, the density is saturated, so there is no sense of incongruity.

  FIG. 20 schematically shows an enlargement of the overlapping of the color colorants by color copying. FIG. 20D shows an ideal case where black characters are processed for all four colors. (E) of FIG. 20 shows a case where black characters are processed for all four colors, and only bk is not corrected, and correction other than bk is applied and lightened. FIG. 20 (f) shows a preferable case where only black characters are processed according to the present embodiment. FIG. 20 (g) shows black characters processed only according to the present embodiment and only bk is not corrected. , Bk is a preferable case where correction is applied.

  FIG. 20A shows an ideal case where the expansion amount is the same and black characters are processed. FIG. 20B shows the case where the expansion amount is the same and the print position is shifted after black character processing (out of white). FIG. 20C shows a case where the printing position is shifted by the black character processing according to the present embodiment when the expansion amount of bk is large.

  The feature quantities used in the comprehensive determination 326 for determining whether the character is in FIG. 25 are the gray determination result (output in FIG. 8), the high density detection result (output in FIG. 8), and the color determination result (b / c signal in FIG. 22). The halftone dot separation result (output in FIG. 12) and the character determination result (character determination output in FIG. 25) are used.

  As shown in FIG. 25, the determination of whether the character is a character consists of a pattern determination, a black determination, two mirrors, extractions 1 and 2, and the internal processing determines whether the character is in three states: a pattern, a character, and black. .

1) Picture determination This is obtained from a feature quantity not included in black characters. If any of the halftone dot separation result, the gray determination result, and the color determination result is active, the pattern is used. When written in a formula, it becomes like the following formula.
Halftone separation result # Gray judgment result # Color judgment result

2) Black determination This obtains a feature amount (dark black) in a black character. The color determination result is not a color, but is black when the high density determination result is dark. When written in a formula, it becomes like the following formula.
! Color judgment result # High density judgment result

3) Extraction A
The extraction unit A determines whether the image is a normal image. The flow of determination in the extraction unit A is shown in FIG. In the line segment processing (step S2601), the black determination result of the previous line is corrected. FIG. 27 shows a flowchart of specific processing of line segment processing. First, the continuous pixel number i = 0 on the line on which line segment processing is performed is set (step S2601). Next, it is determined whether or not the pixel subject to line segment processing is determined to be black in the black determination (step S2702). When the pixel is not determined to be black in the black determination (step S2702 / NO), the state variable array SS [i−j] (the processed line one line before the processing target line) and the target line determination result The line segment processing ends with the black determination result of MS [i−j] being the same (step S2703). On the other hand, when the pixel is determined to be black in the black determination (step S2702 / YES), the black continuous pixel number i in the main scanning direction in the black determination of the target line is detected (step S2704). When the detected number of consecutive pixels i is larger than the threshold value thl (step S2705 / YES), the state variable array SS [i−j] is corrected to the line of the picture area (step S2706). Next, a process for initializing the continuous pixel number i is executed (step S2707, step S2708 / YES). When the continuous pixel number i is not i = 0 (step S2707, step S2708 / NO), the line segment processing is performed again (step S2703). If the number of consecutive pixels i in the main scanning direction is not larger than the threshold thl (step S2704 / NO), the state variable array SS [i−j] and the determination result MS [i−j] of the target line As a result of the black determination, the line segment processing ends (step S2702). With the above processing, if the number of continuous black pixels is larger than the threshold value thl in the black determination, the black pixels are corrected to the picture area. In line segment processing, the line width for detecting characters is defined. For example, if thl is 48 and the number of continuous pixels in the previous line is 48 pixels or more, it is determined that the next line is not a character.

  When the line segment processing is completed (step S2601), the following processing is executed. In the following processing, when a plurality of target pixels match, the top is prioritized. The pixel of interest is detected by the character determination unit 326a or the pattern determination result (step S2602). If it is determined that the character is determined by the character determination result in the character determination unit 326a for image area separation, the character is determined as a region (step S2602 / character). On the other hand, if the result of the picture determination is the picture area, the process in the extraction A is terminated because the target pixel belongs to the picture area (step S2602 / picture). Note that neither characters nor patterns are turned on on the image area separation algorithm. If neither is determined in the character determination unit 326a or the pattern determination, the black determination result of the target pixel is detected (step S2603). When the black determination result of the target pixel is not black (step S2603 / NO), it is determined as an intermediate region. On the other hand, if the result of black determination for the pixel of interest is black (step S2603 / YES), the determination result one line before the line segment processing is detected (step S2604). If the determination result one line before the line segment processing is a pattern area (step S2604 / pattern), the pattern area is determined. On the other hand, when the determination result one line before the line segment processing is other than the pattern (step S2604 / other than the pattern), the determination result one pixel before in the pattern determination is detected (step S2605). If the determination result one pixel before is a picture area (step S2605 / picture), the picture area is set. On the other hand, if the determination result one pixel before is other than the pattern (step S2605 / other than the pattern), the determination result is detected whether the character is one line before the line processing (step S2606). When it is determined that the character is an area before the character (step S2606 / character), the target pixel is determined to belong to the area. On the other hand, if it is determined that the character is one area before the character, the result of the determination is whether the character is one character before (step S2606 / other than the character). If it is determined that the character one pixel before is a character (step S2707 / character), it is determined that the pixel of interest also belongs to the character region. On the other hand, if it is determined that the character one pixel before is not a character (step S2707 / other than a character), the target pixel is determined to be an intermediate region.

4) Extraction B
In the extraction B, it is determined whether the character is an inverse image (mirror) image. Mirroring is performed before and after extraction B in order to realize processing with an inverse image by pipeline processing. FIG. 28 shows a flowchart of processing in extraction B. The difference between Extraction A and Extraction B is the same except that there is no line segment processing, and thus description thereof is omitted. The reason why line processing is not performed is simply to reduce processing. Conversely, even if line width processing is performed during reverse image processing without performing line width processing for normal image processing, the final result (determination signal for characters) is the same.

5) Determination If the result of both extraction A and extraction B is a character or an area, it is determined that the character is a character. Here, since extraction B passes through two mirror circuits, extraction A and extraction B are shifted by two lines. By processing while shifting by two lines, there is no need to increase the delay memory. Here, the character determination signal includes a character edge signal.

  As described above, by referring to the state of the image of the surrounding pixels and determining whether the character is the target pixel, it is possible to determine the character in the size image area. Further, when a halftone dot separation result (printed matter), a color determination result (color), or a gray determination result (printing paper photograph) is made around the peripheral pixels of the high density data, it is not determined that the character is a character. Here, the color is seen because black characters are determined among black characters, and when color characters other than black characters are detected, the color determination result may not be referred to. If different processing is performed for color characters and black characters, the color determination result may be divided into color and non-color (not color). In addition, when there is no halftone dot separation result (printed material), color determination result (color), gray determination result (printing paper photograph) around the altitude data, and there is a character edge, it is determined whether the character is a character. The halftone dot separation result is referred to in order to prevent erroneous determination of a dark black portion in the halftone dot of the printed matter. The reason for referring to the gray determination result is to prevent erroneous determination of a dark portion of the photographic paper photograph. As described above, it is possible to accurately determine the character by referring to the adjacent area of the high density area.

<< Decoding Unit >> The C / P signal finally output by the decoding unit is as follows:
C / P signal Character edge signal Character signal 0 None ×
1 Yes No Character edge region 2 Yes No Character middle region Further, the color determination unit 325 outputs a B / C signal as shown in FIGS.

  Next, FIG. 3 will be referred to again. The C / P signal and B / C signal generated by the document recognition unit 320 are an RGB filter unit 330, a color correction unit 340, a scaling unit 350, an interface unit 352, a UCR unit 360, a CMYBk filter unit 370, and a CMYBkγ correction unit 380. And the gradation processing unit 390 is provided in cascade in synchronization with the image data.

  The RGB filter unit 330 is a filter that performs MTF correction on RGB data, and includes a coefficient matrix corresponding to an N × N pixel matrix and logic that multiplies each coefficient by each image data to obtain a weighted average value. When the C / P signal represents 1 (character edge region), a coefficient matrix for sharpening processing is used, and when it represents 0 or 2 (character region or picture region), it is used for smoothing processing. Using the coefficient matrix, a weighted average value is derived and output to the color correction unit 340. The color correction unit 340 converts R, G, and B data into C, M, and Y data by primary masking processing or the like. The scaling unit 350 performs enlargement / reduction in the main scanning direction x or equal magnification processing on the image data.

  The UCR unit 360 is for improving the color reproduction of the image data, and generates Bk data by performing UCR (additional color removal) processing on the common part of the C, M, and Y data input from the color correction unit 340. , C, M, Y, Bk data is output. Here, when the C / P signal is other than 1 (character edge region) (when it is a character region or a picture region), skeleton black processing is performed. When the C / P signal is 1 (character edge region), full black processing is performed. Further, when the C / P signal is 1 (character edge region) and the B / C signal is H (achromatic region), the C, M, and Y data are erased. This is because black characters are expressed only by the black component.

  In addition, the output image signal IMG of the UCR unit 360 is one color among C, M, Y, and Bk at a temporary point, and is a frame sequential one color output. That is, full-color (four-color) data is generated by reading the document four times. Further, in the case of black-and-white copying, since only one Bk image formation is required, one document reading is sufficient. If there is a mechanism for determining whether the original is a color document or a black and white document, the number of times of reading depends on the document. Therefore, it is not necessary for the operator to determine whether the document is a color document or a monochrome document according to the document. In this embodiment, it is a signal that is referred to in determining whether the B / C signal is a color document or a monochrome document. When the B / C signal is H (achromatic region) on the entire surface of the document, the main controller 10 determines that the document is a monochrome document.

  The CMYBk filter unit 370 performs smoothing and sharpening using an N × N spatial filter according to the frequency characteristics of the color printer 400 and the C / P signal. The CMYBkγ correction unit 380 changes and processes the γ curve according to the frequency characteristics of the color printer 400 and the C / P signal. When the C / P signal is 0 (picture area), a γ curve that faithfully reproduces the image is used. When the C / P signal is 1 (character edge area), the γ curve is set to enhance the contrast. Further, when the C / P signal is 2 (character medium region), a γ curve that is darker than the character edge region is set. By making the γ curve in the character darker than the character edge γ, there is an effect of preventing the data in the character from becoming light.

  The gradation processing unit 390 performs quantization such as dither processing and error diffusion processing according to the gradation characteristics of the color printer 400 and the C / P signal. During Bk image formation, gradation-oriented processing is performed when the C / P signal is 0 (picture area), and resolution-oriented processing is performed otherwise. For image formation other than Bk, gradation-oriented processing is performed when the C / P signal is 0 (picture area), and resolution-oriented processing is performed otherwise. The image data subjected to the above processing is given from the video control 359 having a buffer memory to the color printer 400 in synchronization with the image data writing operation.

  When the image processing (C / P signal = 0), the IPU 300 performs smoothing processing by the RGB filter unit 330, performs skeleton black processing by the UCR unit 360, and linear (gradation characteristics) by the CMYBkγ correction unit 380. ) Is selected, and the CMYBk filter unit 370 and the gradation processing unit 390 perform processing that emphasizes gradation.

  On the other hand, when character processing (C / P signal = 1 and B / C signal = L), the RGB filter unit 330 performs edge enhancement processing, the UCR unit 360 performs full black processing, and the CMYBkγ correction unit 380 performs contrast. The CMYBk filter unit 370 and the gradation processing unit 390 perform processing with emphasis on resolution.

  In black character processing (C / P signal = 1 and B / C signal = H), C, M, and Y data are not printed during C, M, and Y image formation excluding Bk. This is to prevent the surroundings of black characters from being colored due to misalignment. In addition, the RGB filter unit 330 of the Bk data at this time may be sharpened by performing edge enhancement more strongly than in the case of color characters.

  As described above, the IPU 300 performs four types of processing: a pattern, a black character edge, a color character edge, and a character processing.

1 is a schematic configuration diagram of a digital full-color copying machine including an image processing apparatus according to the present embodiment. It is a block diagram which shows the outline | summary of the electric system of the digital full-color copying machine shown in FIG. It is a block diagram which shows the structure of the image processing unit (IPU) in FIG. FIG. 4 is a functional block diagram illustrating a configuration of a document recognition unit in FIG. 3. It is a flowchart which shows the process sequence of the update of state variables MS and SS [I] used for white determination. It is a functional block diagram which shows the content of the color pixel determination part in FIG. It is a flowchart which shows the process sequence of the determination process which determines whether it is a color original or a black-and-white original in the continuous count part in FIG. It is the figure which compares the line pattern of 600 dpi and the line pattern of 400 dpi. FIG. 5 is a diagram illustrating a 3 × 3 pixel matrix pattern used for pattern matching performed by a black pixel continuous detection unit and a white pixel continuous detection unit in FIG. 4. It is a figure which shows the example of a pattern used for the white background separation of the RGB white background detection part in FIG. It is a figure which shows the example of a pattern used at the time of the color ground detection in FIG. It is a figure which shows typically the present line (target line) of the line memory LMP. It is a figure which shows the area | region for demonstrating the process of the white area extraction part in FIG. FIG. 5 is a diagram for explaining a detection process of a first halftone peak detection unit of a halftone dot extraction unit in FIG. 4. It is a figure for demonstrating the process of the color determination part in FIG. It is a figure for demonstrating the pattern matching in the color pixel determination of FIG. It is a figure which shows the pattern for color thin lines which detects the color line enclosed by white. It is a figure which shows the white area | region pattern for performing the pattern matching in which c, m, and y are all 0. It is a figure which shows the specific data of a color pixel continuous number. It is a figure which expands and shows the overlap of the color colorant by color copying typically. It is a block diagram which shows the detail of the white area extraction part in FIG. It is a figure which shows the example of a line pattern and pattern matching pattern for detecting a gray pixel, (a) is a 200 line pattern, (b) is a pattern for 300 lines. It is a block diagram which shows the detail of the halftone dot extraction part in FIG. It is a figure for demonstrating the detection process of a 3rd halftone peak detection part. It is a figure which shows the processing content of the comprehensive determination part in FIG. It is a flowchart for demonstrating the process of character determination. It is a flowchart for demonstrating a line segment process. It is a flowchart for demonstrating the process of character determination.

Explanation of symbols

10 Main Controller 12 Scanner Controller 16 Printer Controller 17 FAX Controller 18 Parallel I / F
19 LAN control 20 Communication controller 40 Image processing unit (IPU)
200 Color image reader (scanner)
300 Image processing unit (IPU)
320 Document Recognition Unit 321 Filter Unit 322 Edge Extraction Unit 323 White Region Extraction Unit 323e Binarization Unit 323b RGB White Extraction Unit 323b-1 Gray Pixel Detection Unit 323b-2 Color Pixel Detection Unit 323b-3 RGB White Background Detection Unit 323c White Determination Unit 323d white pattern matching unit 323g white correction unit 323h gray matching unit 323i gray expansion unit 323j white pattern correction unit 323k white expansion unit 323l white contraction unit 323m determination unit 324 halftone dot extraction unit 324a first halftone peak detection unit 324b second Halftone dot detection section 324c Third halftone peak detection section 324d First halftone area detection section 324e Second halftone area detection section 324f Temporary memory 325 Color determination section 326 Overall determination 330 RGB filter 400 Color image recording apparatus (color printer) )

Claims (9)

In an image processing apparatus that performs predetermined processing on output image data and outputs the processed image data,
A character edge area detecting means for detecting a character edge area of the image data;
Medium density area detecting means for detecting a medium density area of the image data;
Expansion means for expanding the medium concentration area detected by the medium concentration area detection means;
A pattern area detecting means for detecting a pattern area of the image data;
It is determined whether the image data has a character from the character edge area detection result by the character edge area detection means, the medium density area detection result by the medium density area detection means, and the pattern area detection result by the pattern area detection means. Character judging means to perform,
Expansion processing means for expanding the medium concentration area detected by the medium concentration area detection means;
Color determination means for determining the color of the image of the image data;
The image data is contained in the character by the determination result by the character determination unit, the determination result by the color determination unit, the medium density region detected by the medium density region detection unit, and the design area detected by the design region detection unit. An image processing apparatus comprising: determination means for determining whether or not The pattern area detecting means includes
Detecting halftone dots from the image processing target area,
When the halftone dot is not detected, it is determined that the image area is not included in the image processing target area,
The image processing apparatus according to claim 1, wherein when the halftone dot is detected, the image processing target area is determined to include the pattern area.   The image processing apparatus according to claim 1, wherein the character edge area detection unit detects a character on a white background. The medium concentration area detecting means includes
High density area detection means for detecting a high density area from the image data;
Gray pixel detection means for detecting gray pixels from the image data;
The image processing apparatus according to claim 1, further comprising a white area detecting unit configured to detect a white area from the image data.   The determination unit determines that the image data is not in the character when the high-density region detection unit detects the high-density region having a predetermined number of pixels or more. The image processing apparatus according to claim 1. An image processing apparatus according to any one of claims 1 to 5,
An image reading apparatus comprising: reading means for inputting image data generated by color-separating and reading a document image to the image processing apparatus. An image processing apparatus according to any one of claims 1 to 5,
An image forming apparatus comprising: an image output unit that forms an image based on image data output from the image processing apparatus, forms the formed image on a sheet, and outputs the image. An image processing apparatus according to any one of claims 1 to 5,
Reading means for inputting image data generated by color-separating and reading a document image to the image processing apparatus;
A color copying apparatus comprising: an image output unit that forms an image based on image data output from the image processing device, forms the formed image on a sheet, and outputs the image.   9. The color copying apparatus according to claim 8, further comprising control means for analyzing a print instruction command from the outside and printing out image information input from the outside by the image output means.

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