JP7297603B2 - Image processing device, image processing method, and program - Google Patents

Description

The present invention relates to image processing for color conversion of print data.

When outputting a color document expressed in colors such as RGB format in a grayscale format on a normal printing device, a uniform conversion rule for all colors (such as NTSC conversion) is applied to the input RGB values. It is common to convert to grayscale and output.

However, since color information is lost in the process of converting input RGB values to grayscale using a uniform conversion rule, even if different colors have different values in RGB format, the gray values after conversion are It may be the same value or a close value. In such a case, there is a problem that it becomes impossible to discriminate colors after conversion to gray scale, or the discrimination performance deteriorates.

FIG. 1 shows specific examples of a monochrome image with high discrimination and a monochrome image with low discrimination. FIGS. 1A and 1B are both grayscale examples of color pie charts created by spreadsheet software or the like. 1(a) and 1(b) have items P, Q, R, and S, and their distribution is the same. FIG. 1(a) is an example of a highly discriminative pie chart, and the boundaries of each of the four existing items can be clearly recognized. On the other hand, FIG. 1(b) is an example of a pie chart lacking in discrimination, and since the colors of the four items are very similar, it is difficult to clearly recognize the boundaries between the items.

In order to address this problem, Japanese Patent Laid-Open No. 2002-100000 discloses a technique of creating a table for performing highly distinguishable grayscale conversion on a specific color and performing color conversion. In the technique described in Patent Document 1, the gray values after conversion are determined so that the differences between the color values of each of the plurality of colors used in one page are equal when converted to gray. Therefore, for pages that require distinctiveness, color conversion that considers distinctiveness is realized.

JP 2017-38242 A

However, in the method described in Japanese Patent Laid-Open No. 2002-200014, the density of each color in the input color document is converted into gray depends on the number of colors and color scheme for each page, and thus cannot be controlled by the user. I have a problem. For example, even if it is desired to convert the same object, such as a company name, to gray of the same density and print it on all pages, the method described in Patent Document 1 does not allow the same object to be printed in gray after conversion. may differ from page to page.

Therefore, the present invention maintains constant color values after color conversion between pages for specific objects and colors among objects and colors in the same page, and distinguishes other objects and colors after color conversion. The purpose is to improve

The present invention is an image processing apparatus for color-converting color data into monochrome data, and is obtained by applying input tone values of respective colors included in the color data and a conversion rule that maintains the reproducibility of the respective colors. generation means for generating a conversion table in which a first output tone value for each color in the monochrome data obtained is associated with a conversion table; and specifying means for specifying, among objects included in the color data, the first output gradation of the conversion table so as to increase discrimination in the monochrome data of objects other than the object specified by the specifying means. correction means for correcting the value to a second output gradation value; color-converting the color of the specified object according to the conversion table before the correction; and converting the color of the object other than the specified object after the correction. and conversion means for performing color conversion according to the conversion table.

According to the present invention, among the objects and colors on the same page, for specific objects and colors, the color values after color conversion are kept constant between pages, and for other objects and colors, discrimination after color conversion is performed. can improve sexuality.

FIG. 10 is a diagram showing a distinctive case and a non-distinguishable case when a pie chart created by spreadsheet software or the like according to the embodiment is monochromeized. It is a main conversion formula of the gray scale according to the embodiment and a specific calculation result example. 1 is a diagram showing the overall configuration of a print system according to an embodiment; FIG. 2 is a diagram illustrating hardware configurations of a host computer and an image forming apparatus according to the embodiment; FIG. 4A and 4B are diagrams illustrating examples of commands included in print data and drawing results thereof according to the embodiment; FIG. 3 is a diagram showing a software configuration for performing print processing according to the embodiment; FIG. It is a figure which shows the software configuration of the host computer which concerns on embodiment. 4 is a flowchart of control processing of the printer driver according to the embodiment; FIG. 10 is a diagram showing an example of UI for designating a color to the driver according to the embodiment; FIG. 9 is a flowchart of high discrimination processing in grayscale conversion according to the embodiment; FIG. 4 is a diagram relating to a method for determining grayscale values according to an embodiment; FIG. 7 is a diagram showing an example of a conversion table for grayscaling according to the embodiment; FIG. 5 is a diagram showing gray values before and after gray value correction processing according to the embodiment; FIG. 7 is a diagram showing a conversion table used for gray value correction processing according to the embodiment; 4 is a flowchart of grayscale conversion processing according to the embodiment; It is a figure which shows the software configuration of the host computer which concerns on embodiment. FIG. 10 is a diagram showing an example of UI for designating a color to the driver according to the embodiment; FIG. It is a figure which shows the flowchart of the gray value correction process which concerns on embodiment. It is a figure which shows the flowchart of the gray value correction process which concerns on embodiment. It is a figure which shows the flowchart of the gray value correction process which concerns on embodiment. FIG. 5 is a diagram showing gray values before and after gray value correction processing according to the embodiment; FIG. 10 is a diagram showing a UV space used in color value designation processing according to the embodiment;

BEST MODE FOR CARRYING OUT THE INVENTION The best mode for carrying out the present invention will be described below with reference to the drawings.

(Embodiment 1)
FIG. 3 is a diagram showing an example of the overall configuration of the print system. The print system includes at least a host computer 100 and an image forming apparatus 110 . In the example shown in FIG. 3, the host computer 100 and the image forming apparatus 110 are communicably connected to each other via a network 120 such as LAN or WAN. However, the form of connection between the host computer 100 and the image forming apparatus 110 is not limited to this, and may be a local connection using a USB cable or the like. Moreover, each of the host computer 100 and the image forming apparatus 110 may be a single device or a system composed of a plurality of devices as long as the functions of the present invention are realized.

FIG. 4 is an example of a printing system according to the present invention, and is a functional block diagram of the host computer 100 and the image forming apparatus 110. As shown in FIG.

A host computer 100 is connected to an image forming apparatus 110 via a network 120 and comprises a control section 101 , an image processing section 102 , a CPU 103 , a RAM 104 and a storage section 105 . The control unit 101 controls the host computer 100 in a centralized manner, and uses the CPU 103 and the RAM 104 to control the image processing unit 102 as well as applications and printer drivers (not shown) installed in the host computer 100 . In addition to the blocks shown in FIG. 4, blocks necessary for executing the functions of the image forming apparatus 110 and the host computer 100 are included as appropriate.

The image forming apparatus 110 is an example of an image processing apparatus according to the present invention, and is, for example, a multifunction peripheral (MFP: Multi-Function Peripheral) in which multiple functions such as a scanning function and a printer function are integrated. A control unit 111 controls the image forming apparatus 110 in an integrated manner, and includes a CPU 115 , a RAM 116 , a storage unit 117 , an apparatus control unit 112 and an image processing unit 113 . The CPU 115 develops a program stored in the storage unit 117 in the RAM 116 and executes it, thereby controlling the operation of the image forming apparatus 110 . A RAM 116 is a temporary storage memory, and can temporarily store image data, programs, and the like. A storage unit 117 is, for example, a hard disk (HDD), and stores parameters for controlling the image forming apparatus 110, applications, programs, OS, and the like for realizing control according to the embodiment. A device control unit 112 is a device controller, and controls portions connected to the control unit 111 such as an operation unit 114 , an image reading unit 118 and an image output unit 119 . The image reading unit 118 is, for example, a scanner, and the image output unit 119 is, for example, an image forming apparatus. The CPU 115 executes the above-described programs to perform a scan function of acquiring image data of a document read by the image reading unit 118, and an output of outputting an image to a recording medium such as paper or a monitor through the image output unit 119. function is realized.

The image processing unit 113, for example, reads image data stored in the storage unit 117, and performs various image processing for optimizing the image data according to parameters. Image processing is also performed based on setting information notified from the operation unit 114 . Processing for converting a color image into a gray image is also performed here. The operation unit 114 includes a touch panel, hardware keys, and the like, receives instructions and setting operations from the user, and displays device information of the image forming apparatus 110, job progress information, and various user interface screens. Setting information and the like received by operation unit 114 are stored in storage unit 117 via device control unit 112 .

FIG. 5A is a diagram illustrating a command included in print data received by the image forming apparatus 110 according to the first embodiment, an example of conversion thereof, and an example of drawing results based thereon. Commands include drawing commands and control commands, and a drawing command 1400 shows an example of the drawing commands. An image 1407 rendered using this rendering command 1400 is shown in FIG.

The drawing command 1400 includes a color setting command 1401 for setting the color mode of the job and a color setting command 1402 for setting the color. Further, there are an object drawing command 1403 for drawing an object, a character size setting command 1404 for setting a character size, a font setting command 1405 for setting a character font, and a character drawing command 1406 for drawing a character. The configuration of these series of commands is the same for other objects and character strings. In addition, commands for setting coordinates and line thickness, commands for drawing images, etc. are also included, but they are omitted.

The contents of this drawing command 1400 will be briefly described. It should be noted that the rendering command 1400 and color value data that follow are assumed to be an 8-bit image.

A color setting command 1401 "Set Page Color (CL)", which is the second command in FIG. 5A, indicates that the following commands are rendered in full color. The color setting command 1402 "Set Color (146, 208, 80)", which is the third and fourth commands in FIG. It shows that An object drawing command 403 "Draw Polygon" indicates drawing of a figure. As a result, object 1408 is rendered in green with R=146, G=208, and B=80.

Next, the character size setting command 1404 "SetText Size (6)", which is the fifth to twelfth commands in FIG. 5A, indicates that the character size is 6 points. A font setting command 1405 “Set Font (Arial)” indicates that the font of characters is Arial. A character drawing command “Draw Text (“x”)” indicates drawing a character “x”. As a result, the character string "1.xxx" 409 is drawn in cyan with R=0, G=255, and B=255 in Arial font, 6-point character size.

Furthermore, the 13th to 16th commands in FIG. 5(a) indicate that the sun 1410 is drawn in red.

Finally, the 17th to 24th commands in FIG. 5(a) indicate that the character string "2.xxx" 1411 is drawn in black in Arial font, 6-point character size.

FIG. 6 is a diagram illustrating a software configuration for performing print processing in the print system according to the first embodiment.

An application 601 and a printer driver 602 are installed in the host computer 100. In the host computer 100, the application 601 is used to create electronic data such as documents and presentation documents. A printer driver 602 is a driver for outputting print data (color image data) to the image forming apparatus 110 for printing. The print data created by the printer driver 602 is sent to the image forming apparatus 110, processed by the image processing unit 113 of the image forming apparatus 110, and printed.

When receiving the print data, the image forming apparatus 110 causes the command determination unit 603 to determine the PDL type. This PDL type includes PostScript (PS), Printer Command Language (PCL), and the like. The command analysis unit 604 exists for each PDL type, and extracts and analyzes commands of the PDL type specified by the command determination unit 603 . Graying processing or the like is performed according to the content of the command analyzed in this way.

A command execution unit 605 generates a raster image according to the analysis result of the command analysis unit 604 . An image adjustment unit 606 applies image processing such as color conversion and filtering to the raster image. Note that the functions of the command determination unit 603, the command analysis unit 604, the command execution unit 605, and the image adjustment unit 606 of the image processing unit 113 shown in FIG. .

FIG. 7 is a block diagram showing the software configuration of the printer driver 602 on the host computer 100 according to this embodiment. The software configuration of the printer driver 602 will be described below with reference to FIG.

A print setting acquisition unit 701 acquires and holds various print setting information for the printer driver 602 . Various print setting information includes setting information for image processing such as Nup, which prints multiple pages of data on one page, scaling, etc., in addition to drawing contents, and setting information necessary for creating a preview image. Point.

A preview image generation unit 702 creates a preview image from the information held by the print setting acquisition unit 701 described above.

The target area specifying unit 703 allows the user to specify an area for enhancing color discrimination while displaying a preview image on the operation unit 114 or the like, and provides area information indicating the position of the area on the preview image specified by the user. Get and hold. How to specify the area will be described later with an example shown in FIG.

A target object determining unit 704 compares the position of each object with the area information specified by the target area specifying unit 703, and determines whether or not each object is to be a target for improving distinguishability.

A grayscale conversion unit 705 performs weighted grayscale conversion processing such as the NTSC method on all colors included in all pages based on the print setting information.

A gray value correction unit 706 performs gray value correction to improve color distinguishability with respect to a conversion table used for an object determined by the target object determination unit 704 as a target for improving distinguishability.

The print instruction unit 707 acquires print setting information and notifies the image forming apparatus 110 of the print setting information as a print instruction.

In the present disclosure, increasing color discrimination means expanding at least the narrowest gradation value among adjacent gradation values in the order of magnitude of a plurality of gray values included in a monochrome image. shall mean correcting the gray values so that

FIG. 8 is a flowchart showing grayscale conversion processing when high discrimination printing is designated by the printer driver 602 of the host computer 100 .

In step S801, the print setting acquisition unit 701 of the printer driver 602 acquires print setting information including scaling settings and Nup information. A print setting acquisition unit 701 acquires print setting information necessary for this control from the user interface of the printer driver 602 or a print instruction from the OS.

In step S<b>802 , the preview image generation unit 702 of the printer driver 602 generates a print preview image using the print setting information acquired by the print setting acquisition unit 701 .

In step S803, the target area specifying unit 703 of the printer driver 602 causes the user to specify an area including an object whose distinguishability is desired to be enhanced in the preview image of each page, as illustrated in FIG.

In S<b>804 , the target area specifying unit 703 acquires area information indicating the position of the area specified by the user on the preview image for each page in step S<b>803 .

In S805, the target object determination unit 704 of the printer driver 602 selects one object and performs target object determination processing consisting of S806 and S807, and repeats the processing until all objects are subjected to the target object determination processing.

In S806, the target object determination unit 704 compares the area information acquired in S804 with the position information of the object selected in S805, and determines whether the selected object is within the user-designated area. If the object is within the user-specified area and is the target object, the process proceeds to S807. On the other hand, if the object is not within the user-specified area and is an object other than the target object, the process advances to S805.

Here, "within the user-designated area" means that "the object is within the user-designated area" when the user-designated area and the circumscribing rectangle of the object overlap even a little. This takes into account the difference between the drawing range of the object visible on the preview image and the drawing range of the object on the data. In a typical example, an object with a background color (e.g. white) on the outside of the object may have a wider drawing range on the data than the drawing range visible to the user. is.

In S807, if the selected object is within the user-specified area, the target object determination unit 704 adds a flag indicating that the object is a target for enhancing color discrimination.

When target object determination processing for all objects is completed, in step S808, the grayscale conversion unit 705 of the printer driver 602 performs weighted grayscale conversion processing for all colors included in all pages based on the print setting information. conduct. That is, conversion is performed by using the gradation value of each color included in the color data as the input gradation value and the gradation value of each color in the monochrome data as the output gradation value. Instead of performing weighted grayscale conversion processing, a conversion table in which color values of color data and grayscale color values are associated with each other may be used.

In S809, the gray value correction unit 706 of the printer driver 602 selects one page and performs the gray value correction processing of S810, repeating until all pages are selected.

In step S810, the gray value correction unit 706 refers to the flag assigned in step S807, and performs gray value correction processing for increasing the distinguishability only on the conversion table applied to the target object for which the distinguishability is to be improved in the selected page. A specific processing example will be described later with reference to FIG.

In S811, the grayscale conversion unit 705 performs grayscale conversion of the target object of the color data according to the conversion table in which the gray value is corrected and created in S809. As an example, grayscale conversion using the corrected conversion table shown in FIG. 12 will be described. That is, the number of colors used in the object in the user-designated area is 7, and the corrected gray values are determined as G _min =32 and G _max =223 by the determination method of FIG. 11(c). The gray value _C4 , which is the fourth lowest NTSC-converted gray value among the colors contained in the flagged object, is converted to the gray value _G4 "128" corresponding to _C4 in the table.

FIG. 9 shows an example of a user interface (UI) displayed by the printer driver 602 to prompt the user to specify an area containing an object whose color discrimination is desired, and an example of user input. 9A to 9D show four types of UIs, and preview images (900, 910, 920, 930) generated in S802 are displayed in all of the UIs.

FIG. 9A shows an example of a UI for allowing the user to input the top, bottom, left, and right coordinates of a designated region to be designated, and FIG. This is an example in which the user selects a specified area from among the divided areas. FIG. 9(c) is an example in which the user is prompted to input the width and height of the specified area to be specified and the position coordinates that define the relative position between the specified area and the preview image, for example, the position coordinates of the center of the area. FIG. 9D shows an example of inputting a specified area by drawing a line surrounding an arbitrary area on the preview image using a touch panel such as a tablet terminal.

Further, in the present embodiment, it is possible to select whether to enhance the distinguishability for the specified area or to enhance the distinguishability for the unspecified area. As a specific example, it can be specified by a selection button as indicated by 901 in FIG. 9A.

FIG. 10 is a flowchart showing the details of the gray value correction processing in S810. Here, the gray value correction processing is performed to equalize the intervals between adjacent gray values, thereby improving the portion with the poorest discrimination. described as

In S1001, the gray value correction unit 706 extracts gray values included in all flagged objects for each page, and counts the number N of colors.

In S1002, the gray value correction unit 706 sets the maximum value (G _max ) and minimum value (G _min ) of the corrected gray value after the gray value correction process. As will be described later after S1002, these G _max and G _min are the minimum and maximum values after gray value correction. There are roughly four methods for determining G _max and G _min . FIGS. 11A to 11D show an example of a gray value determination method when the number of colors N is seven.

FIG. 11(a) shows a method in which the corrected gray values G _min and G _man are determined to be "0" and "255", respectively, when the gray value is 256 gradations. This method makes the most extensive use of gray values. However, in this method, one of the colored portions is assigned to "255" (white), which is highly likely to be the same as the background color.

On the other hand, FIG. 11B shows a division method for avoiding such a situation, in which G _min is set to "0" and G _max is divided into 7 (=N) of "255" and 6 (= N-1) The gray value for the division, ie "219".

FIG. 11(c) is a method of determining G _min so that the intervals between adjacent gray values are equal, similar to G _max in FIG. 11(b). That is, 255 is divided into 8 (=N+1), the gray value "32" for one of the divisions is set to G _min , and the value "224" is obtained by adding the gray value for 6 (=N−1) divisions to G _min. be _Gmax .

Finally, FIG. 11D shows a method of setting G _min and G _max according to the number N of colors.

The selection method of FIGS. 11(a) to 11(d) will be described below with more specific examples. Here, it is assumed that the NTSC method (FIG. 2A) is used for grayscale conversion common to all pages performed in S808. 11A or 11B is selected when the minimum value is 0 when grayscale conversion is performed on the RGB values contained in the print data, and when the maximum value is 255, 11(a) or set G _max to 255. If there is neither 0 nor 255, then FIG. 11(c) is selected. Also, even if FIG. 11(c) is set, if the gradation value difference (G _max −G _min ) is smaller than the number of colors, then FIG. 11(d) is used.

In S1003, based on G _mix and G _max determined in S1002 and the number of colors N counted in S1001, the gray value correction unit 706 divides G _max −G _min by (N−1) to divide the gray values. Correction gray values G ₁ to G _N are calculated so as to be approximately equal. Note that G ₁ is G _max and G _N is _{G min} .

In S1004, the gray value correction unit 706 converts corrected gray values that associate the corrected gray values G ₁ to G _N calculated in S1003 with the original gray values C ₁ to C _N before correction for each object. Create a table.

Here, the case where the corrected gray values G ₁ to G ₇ are determined according to the G _min and G _max determination method of FIG. 11(c) will be described with reference to FIG. The gray value gradation number 255 is divided into 8 (=N+1), and the gray value "32" for one division is added to G _min to obtain "32", "64", ..., "224". Seven gray values are defined as corrected gray values, G ₁ , G ₂ , . . . , G ₇ (1203 in FIG. 12). Also, among the gray values converted to gray scale in S808, _the gray values of the colors included in the flagged object are C ₁ , C ₂ , . Then, a corrected conversion table (correspondence table) that associates the original gray values and the corrected gray values with _C1 and _G1 , _C2 and _G2 , . . . , _C7 and _G7 is created. Note that a corrected conversion table for grayscale conversion may be obtained by adding correction gray values to the conversion table created in S808.

As described above, in this embodiment, the user is allowed to specify an area for enhancing color discrimination, and gray values are corrected only for objects within the area specified by the user, and all objects in other areas are corrected. It becomes possible to protect the reproducibility of colors on the page. This makes it possible to improve color discrimination and maintain reproducibility within the same page.

In the above embodiment, the configuration in which the printer driver 602 of the host computer 100 performs the color conversion process has been described. Also, an area to be subjected to grayscale conversion with high discrimination or an area to be subjected to grayscale conversion with reproducibility in which the color after conversion is constant for all pages is specified from the operation panel of the image forming apparatus 110. You may make it possible.

(Embodiment 2)
In the present embodiment, a color to be subjected to grayscale conversion is designated with the same weighting on any page, and gray value correction processing is performed to improve distinguishability of colors other than the designated color. FIG. 15 shows a flowchart of grayscale conversion processing according to the second embodiment. Further, FIG. 18 shows a flowchart of gray value correction processing according to the second embodiment.

Here, a case where this embodiment is applied to the specific example shown in FIG. 5B will be described. The red color of the sun 1410 is always assigned the same gray value, and the green, cyan, and black colors of the other objects 1408, 1409, and 1411 are assigned gray values at distinct intervals.

The processes shown in FIGS. 15 and 19 are also achieved by causing the CPU 103 of the host computer 100 to expand the program stored in the storage unit 105 into the RAM 104 and executing the expanded program in the image processing unit 102. FIG. Further, in the grayscale conversion processing in which the RGB values are weighted, as in the first embodiment, the result of weighting the RGB values of 0.299R+0.587G+0.114B is set as the gray value. Describe.

First, in S<b>1601 , the printer driver 602 of the host computer 100 acquires color values (RGB values) saved in the RAM 104 . The color values obtained here are colors that are subjected to grayscale conversion with the same weighting on all pages. Hereinafter, this color will be called a specified color. A method of specifying a specified color will be described later in <color value specifying process>.

Next, in S1602, the CPU 115 analyzes the color setting command 1402 for each page in the command analysis unit 604, and extracts the color values (RGB values) specified by the color setting command 1402 for each page. The extracted color values are added to the conversion table 1500 shown in FIG. 14(a). A conversion table 1500 is created for each page and holds RGB values, which are extracted color values. If the same color value as the color value extracted from the color setting command 1402 is already stored in the conversion table 1500, it is not added to the conversion table 1500. FIG. When the conversion table 1500 for each page is completed, the CPU 115 stores the conversion table 1500 for the number of pages in the RAM 116 .

Next, in S<b>1603 , the grayscale conversion unit 1704 performs grayscale conversion on all the extracted RGB values with weighting, calculates the corresponding gray values, and registers them in the conversion table 1500 .

After that, in S1604, the gray value correction unit 1705 selects one page, performs the gray value correction processing of S1605, which will be described later, on the selected page, and repeats the processing until all pages are processed. The corrected conversion table 1500 is retained until all pages have been processed. If the page-by-page conversion table 1500 is held until the processing for all pages is completed, the conversion table 1500 is created for the number of pages. The above processing is repeated, and when all pages are completed, the gray value correction processing ends.

In S1606, the grayscale conversion unit 1704 performs grayscale conversion of the color data according to the conversion table created in S1604 and in which the gray values are corrected.

Note that when the processing of S1606 is performed in S1604, the corrected conversion table 1500 for each page generated in S1605 does not hold the conversion table 1500 for each page, and when the next page is selected, the previous conversion table 1500 is changed. You can overwrite information on the page.

FIG. 18 shows a flowchart of the gray value correction processing in S1605 of this embodiment.

First, in S1901, the gray value correction unit 1705 reads the conversion table 1500 of the selected page stored in the RAM 116, extracts colors other than the specified color acquired in S1601 from the conversion table 1500, count the number.

Since S1902 to S1904 are the same processing as S1002 to S1004 of the first embodiment, the explanation is omitted here. However, the correspondence table between the corrected gray values and the original gray values is the conversion table 1500 in which the corrected gray values are registered, and the conversion table 1500 updated by the CPU 115 is stored in the RAM 116 .

In S1905, the gray value correction unit 1705 reads out the updated conversion table 1500 and the input image of the selected page from the RAM 116, and converts the input document into a grayscale image according to the conversion table 1500. FIG.

A specific example of the gray value correction process for improving the distinguishability performed in this flow will be described later in <Gray value correction process for improving the distinguishability>.

<Color value specification processing>
Next, the designated color setting process performed in S1601 will be described with reference to FIGS. 16 and 17. FIG.

FIG. 16 is a block diagram showing the software configuration of the printer driver 602 of the host computer 100 according to this embodiment. The software configuration of the printer driver 602 according to this embodiment will be described below with reference to FIG.

A designated color setting unit 1700 that performs designated color setting processing is implemented by the CPU 103 of the host computer 100 via the printer driver 602 . As shown in FIG. 16, the specified color setting unit 1700 includes a print setting acquisition unit 1701, a preview image generation unit 1702, a specified color acquisition unit 1703, a gray scale conversion unit 1704, a gray value correction unit 1705, and a print instruction unit 1706. . A print setting acquisition unit 1701, a preview image generation unit 1702, a grayscale conversion unit 1704, a gray value correction unit 1705, and a print instruction unit 1706 have the same configuration as the printer driver 602 of the first embodiment. That is, they are the same as the print setting acquisition unit 701, preview image generation unit 702, grayscale conversion unit 705, gray value correction unit 706, and print instruction unit 707 shown in FIG.

The preview image generator 1702 displays a preview image as shown in FIG. 17B on the display device to which the host computer 100 is connected.

A specified color acquisition unit 1703 acquires the RGB values of a specified color specified by the user. For example, RGB values are obtained from the user via a UI 1801 as shown in FIG. 17(a). For example, color values are preset such as "red 1802" = (255, 0, 0), "blue 1803" = (0, 0, 255), etc. associated with RGB values as shown in Fig. 17(a). It may be specified by having the user select a button.

When the user designates an arbitrary area on the displayed preview image, the designated color obtaining unit 1703 obtains a color other than white or black in the designated area. For example, when the user designates an area 1804 shown in FIG. 17B, the color values other than white or black included in the object in that area 1804 are acquired. This way you can get multiple colors at the same time. A region 1804 is a rectangle surrounding the upper left vertex and the lower right vertex. You can specify by clicking each vertex.

A designated color acquisition unit 1703 reads from the RAM 104 the color value of the designated color previously held in the RAM 104 . For example, commonly used colors such as (R, G, B)=(255, 0, 0) are stored in the RAM 104 in advance, and the colors are held automatically as specified colors or according to user input. read out. Alternatively, the information registered in advance by the user may be held in the RAM 104 and read out.

The print instruction unit 1707 acquires print setting information and notifies the image forming apparatus 110 of the print setting information as a print instruction. Here, the specified color acquired by the specified color acquisition unit 1703 is acquired as print setting information by the print instruction unit 1707 along with settings such as monochrome output. The acquired print setting information is sent from the host computer 100 to the image forming apparatus 110 as a print instruction, and is stored in the RAM 116 by the CPU 115 of the image forming apparatus 110 .

As a method for setting the designated color, as described above, a method of directly inputting the RGB values by the designated color acquisition unit 1703, or a method of displaying buttons such as red and blue associated with the RGB values and allowing the user to select There is a method of using the color associated with the selected button as the specified color. Alternatively, the specified color may be set by acquiring the color of the pixel on the preview image specified by the user using the specified color acquisition unit 1703 . Alternatively, the designated color may be set by calling a predetermined designated color from the designated color acquisition unit 1703 . If at least one of these is used, the specified color can be set.

<Gray value correction processing for improving discrimination>
Next, an example of grayscale conversion processing performed on a color whose distinguishability is desired to be improved will be described with reference to FIGS. 13 and 14. FIG. Here, grayscale conversion is performed with the same weight for all colors including the designated color, and then the gray values of colors other than the designated color are corrected for each page to improve the distinguishability of colors other than the designated color. I will explain how.

FIG. 14(a) shows a conversion table 1500 created by the gray value correction processing of S1605. When the RGB values (146, 208, 80) of the object 1408 in FIG. 5(b) are weighted and grayscale-converted using the NTSC method, the gray value is "175", and the gray value of the object 1409 is "179". is.

1300 in FIG. 13 shows the gray values calculated by this weighted grayscale conversion. FIG. 13 shows the interval between the gray values of colors including the gray value 1301 ("255") of the white background (background of the document) and the gray value 1304 ("0") of black used for characters. Intervals 1306-1308. Among the intervals 1306 to 1308, the narrowest interval 1307 is the point with the worst discrimination.

By performing gray value correction processing for improving the distinguishability of the present embodiment on such gray values 1301 to 1304, intervals 1306 to 1308 of gray values are corrected. The interval 1306 (“76”) is the interval between the gray value 1301 (“255”) of the white background (original background) and the gray value 1302 (“179”) of the object 1409 . Interval 1307 (“4”) is the interval between gray value 1302 (“179”) of object 1409 and gray value 1303 (“175”) of object 1408 . Interval 1308 (“175”) is the interval between gray value 1303 (“175”) of object 1409 and gray value 1304 (“0”) of black.

In the gray value correction processing for improving the distinguishability of this embodiment, as in the first embodiment, correction is made so that these intervals 1306 to 1308 are equal. Evenly dividing the possible gray values from “0” to “255” by the three intervals 1306 to 1308 between the four gray values 1301 to 1304 gives 255/3=85. Therefore, the gray values 1302 and 1303 are corrected to corrected gray values 1302' and 1303' so that the intervals 1306 to 1308 are "85" respectively.

1300' in FIG. 13 shows the corrected gray value. Gray value 1302 (“179”) of object 1409 became gray value 1302′ (“170”), and gray value 1303 (“175”) of object 1408 became gray value 1303′ (“85”). This equalizes the spacings 1306-1308, and this process widens the narrowest spacing 1307 ("4") to spacing 1307' ("85"), improving the discrimination between objects 1408 and 1409. I am able to do it.

In the present embodiment, a method has been described in which colors other than the designated color are subjected to weighted grayscale conversion using the same conversion rule as the designated color, and the calculated gray value is corrected to improve distinguishability. However, grayscale conversion by weighting using a conversion rule different from that for the designated color may be performed on colors other than the designated color, and the calculated gray value may be corrected.

In the present embodiment, the designated color can be subjected to grayscale conversion with the same weight regardless of the page, and the colors other than the designated color can be subjected to grayscale conversion that enhances the distinguishability. As a result, it is possible to always output a specified color with a uniform gray value for each page, such as a logo or headline, at a constant density, and to improve the distinguishability of colors other than the specified color.

In the present embodiment, the same weighting is applied to all pages, and colors are specified for which the same grayscale conversion is performed on all pages. You may specify the color for which gray value correction is to be performed. In that case, it can be realized by performing gray value correction processing for improving the distinguishability only for the specified color.

In addition, in the present embodiment, the grayscale conversion process for assigning the same weight to all pages is performed by weighting the RGB values according to the conversion rule of 0.299R+0.587G+0.114B shown in FIG. However, other weighting factors have the same effect.

Also, when specifying red 1802 or the like described with reference to FIG. If the surrounding colors are also designated as the designated colors, the user's troublesome operation of designating the colors can be reduced.

For example, when red 1802 in FIG. 17A is selected, the shaded area 2301 of the UV space shown in FIG. 22 is set, and when blue 1803 is selected, the shaded area 2302 is set, and green is similarly selected. and 2303 may be set. In this case, in the specified color determination process (S1901), the RGB values of the input document are converted into YUV values, and it is determined whether or not the color is within a predetermined specified color area. can judge.

(Embodiment 3)
Embodiment 2 is a method in which the designated color is a gray value converted to gray scale with the same weight regardless of the page, and the gray value is corrected so as to improve the distinguishability of colors other than the designated color. In this case, since the interval between the gray value of the designated color and the gray value of the color other than the designated color is not corrected, the discrimination between them may remain low.

In the present embodiment, when the gray value of such a designated color and the gray value of a color other than the designated color are less distinguishable, gray value correction is performed to improve the distinguishability. The description of the configuration common to the second embodiment will be omitted, and only the configuration that is different will be added.

In this embodiment, the grayscale conversion process of FIG. 15 is performed in the same manner as in the second embodiment. Since only the gray correction processing in S1603 differs from the second embodiment, only the details of the gray value correction processing of this embodiment will be described with reference to FIGS.

FIG. 19 shows the gray value correction processing performed in S1603 of this embodiment.

In S<b>2001 , the gray value correction unit 1705 reads the conversion table 1500 stored in the RAM 116 . Then, the gray value correction unit 1705 extracts colors other than the specified color acquired in step S1601 from the conversion table 1500, the number NA of colors larger than the gray value Cs of the specified color, and the number of colors smaller than the gray value Cs. Count the number NB.

In S2002, the gray value correction unit 1705 sets the maximum value (G _max ) and minimum value (G _min ) of the corrected gray value after the gray value correction process, as in S1002.

In S2003, the gray value correction unit 1705 determines whether one of the numbers of colors NA and NB is 0. If either one of the numbers of colors NA and NB is 0, the process proceeds to S2004; otherwise, the process proceeds to S2005.

In S2004, if NB=0, the gray value correction unit 1705 NA-divides (G _max −Cs) to calculate the corrected gray value. When NA=0, (Cs−G _min ) is divided by NB to calculate the corrected gray value.

In S2005, the gray value correction unit 1705 divides (G _max −Cs) into NA to calculate NA corrected gray values, and divides (Cs−G _min ) into NB to calculate NB corrected gray values. calculate.

Since S2006 and S2007 are the same processing as S1904 and S1905, description thereof is omitted here.

Next, an example of grayscale conversion processing for improving discrimination performed in this embodiment will be described. In the gray value correction processing for improving the distinguishability of the present embodiment, unlike the second embodiment, gray value correction is performed in consideration of the designated color.

Therefore, 2200 in FIG. 21 shows a state in which not only the gray values of the objects 1408 and 1409 but also the gray value of the object 1410, which is the designated color, is taken into account.

Here, the intervals of each color including the gray value "255" (2201) of the white background (background of the document) and the gray value "0" (2205) of the black of the object 411 are intervals 2206 to 2209 shown in FIG. be. Among the intervals 2206 to 2209, the narrowest interval 2207 is a portion with relatively poor discrimination. Note that the example shown in FIG. 21 corresponds to the case of NB=0, so the processing of S2004 is performed.

By performing the grayscale conversion process for improving the distinguishability of the present embodiment on such gray values 2201 to 2205, the intervals 2206 to 2208 of the gray values are corrected. That is, in this embodiment, correction is made so that the intervals 2206 to 2208 between the gray value "255" (2201) of the white background (background of the original) and the gray value "76" (2204) of the object 1410, which is the designated color, are equal. do.

2200' in FIG. 21 shows the corrected gray values. The gray value of object 1409 has gone from '179' (2202) to '194' (2202'), and the gray value of object 1408 has gone from '175' (2203) to '135' (2203'). By this processing, the interval 2207, which is a portion with poor discrimination, is changed from "4" to "59" (2207'), and the discrimination between the object 1408 and the specified color can be improved compared to the second embodiment.

The gray value of the object 1410, which is the specified color, is "76" (2204), and the gray value of the object 1408 "135" (2203') is "59" (2208'). Yes, and distinctiveness is ensured.

It should be noted that the threshold value of the gray value interval that defines the goodness or badness of discrimination may be changed according to the number of colors used in the page for possible gray values from "0" to "255".

As described above, the specified color is calculated by weighted grayscale conversion, and other than the specified color, the gray value is calculated so that the interval between gray values less than the threshold is equal to or greater than the threshold, including the interval between the specified color and the gray value of the specified color. This is done by correcting the

In this embodiment, by changing not only the gray value interval of colors other than the designated color but also the gray value interval between the designated color and the colors other than the designated color, the designated color and colors other than the designated color are discriminated. can improve sexuality.

(Embodiment 4)
In Embodiments 2 and 3, the method for improving the distinguishability when there is one specified color has been described. If the value difference is small, their distinctiveness remains small.

In the fourth embodiment, a case where there are two or more designated colors will be described. The description of the configuration common to the second or third embodiment will be omitted, and only the configuration that is different will be added.

This embodiment is another embodiment of the gray value conversion processing in S1603 of FIG. 15, and is a gray scale conversion processing that can improve the distinguishability between designated colors when there are two or more designated colors.

FIG. 20 shows a flowchart showing the gray value conversion process according to this embodiment. Here, a case where there are two designated colors will be described.

In S2101, the gray value correction unit 1705 reads out the conversion table stored in the RAM 116, extracts the gray values Csa and Csb of the specified color acquired in S1601 from the conversion table 1500, and calculates the absolute value of the difference in gradation value | Calculate Csa-Csb|.

In S2102, the gray value correction unit 1705 determines whether |Csa-Csb| If the interval between the gray values Csa and Csb of the designated color is less than the threshold D, the process advances to S2103, and if the interval between the gray values Csa and Csb of the designated color is greater than or equal to the threshold D, the process advances to S2104.

In step S2103, the gray value correction unit 1705 sets corrected gray values Gsa and Gsb whose interval is equal to or greater than the threshold value D with respect to the gray values Csa and Csb of the specified color. The processing of S2103 needs to be performed only once because the same processing is performed for all pages.

In S2104, the gray value correction unit 1705 reads the conversion table 1500 stored in the RAM 116, and extracts colors other than the specified color acquired in S1601 from the conversion table 1500. FIG. Then, the number NA of colors larger than the gray value Csa or Gsa of the specified color, the number NB of colors smaller than the gray value Csa or Gsa and larger than Csb or Gsb, and the number NC of colors smaller than Csb or Gsb to count.

In S2105, the gray value correction unit 1705 sets the maximum value (G _max ) and minimum value (G _min ) of the corrected gray value after the gray value correction process, as in S1002.

In S2106, the gray value correction unit 1705 determines whether any one of the numbers of colors NA, NB, and NC is 0. If any of the numbers of colors NA, NB, and NC is 0, the process proceeds to S2107; otherwise, the process proceeds to S2108.

In S2107, the gray value correction unit 1705 calculates corrected gray values as follows. If NA≠0, (G _max -Csa) or (G _max -Gsa) is NA-divided to calculate the corrected gray value. If NB≠0, (Csa-Csb) or (Gsa-Gsb) is NB-divided to calculate the corrected gray value. If NC≠0, (Csb-G _min ) or (Gsb-G _min ) is NC-divided to calculate the corrected gray value. The gray value correction unit 1705 calculates the corrected gray value for those of NA, NB, and NC that are not 0, and combines the calculated values to obtain the entire corrected gray value.

In S2108, the gray value correction unit 1705 calculates corrected gray values as follows. The gray value correction unit 1705 divides (G _max −Csa) or (G _max −Gsa) into NA, divides (Csa−Csb) or (Gsa−Gsb) into NB, divides (Csb−G _min ) or (Gsb −G _min ) is NC-divided and combined to calculate the corrected gray value.

Since S2109 and S2110 are the same processing as S1904 and S1905, description thereof is omitted here.

In this way, by performing the distinguishability improvement process even between the designated colors, the distinguishability between the designated colors is improved. Furthermore, as in the third embodiment, by adding the designated color and performing the distinguishability improvement processing of S2103 for colors other than the designated color, it is possible to improve the distinguishability between the designated color and the colors other than the designated color.

In the first to third embodiments, the grayscale data is assumed to be corrected, but it is needless to say that the same effect can be obtained even if the correction process is performed on the monochrome data represented by one gradation value. stomach.

(Other examples)
The present invention supplies a program that implements one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and one or more processors in the computer of the system or device reads and executes the program. It can also be realized by processing to It can also be implemented by a circuit (for example, ASIC) that implements one or more functions.

100 Host computer 110 Image forming apparatus 120 Network 701 Print setting acquisition unit 702 Preview image generation unit 703 Target area designation unit 704 Target object determination unit 705 Gray scale conversion unit 706 Gray value correction unit

Claims (21)

An image processing device that performs color conversion from color data to monochrome data,
The input gradation value of each color included in the color data is associated with the first output gradation value of each color in the monochrome data obtained by applying a conversion rule that maintains the reproducibility of each color. generating means for generating a conversion table;
designating means for designating a specific object among the objects included in the color data based on a user input;
The first output gradation value of the conversion table is changed to a second value so as to increase the discrimination in the monochrome data of objects other than the object specified by the specifying means among the objects included in the color data. a correction means for correcting the output gradation value;
conversion means for converting the color of the designated object according to the conversion table before correction, and converting the color of the object other than the designated object according to the conversion table after correction;
An image processing device comprising: 2. The image processing apparatus according to claim 1, wherein said specifying means causes display means to display a preview image of said color data and a specified area including said specific object. 3. The image processing apparatus according to claim 2, wherein said specifying means acquires positional coordinates of vertices of said specified area as said user input. 3. The image processing apparatus according to claim 2, wherein said designating means further acquires position coordinates defining the width and height of said designated area and the relative position between said designated area and said preview image. The specifying means causes the display means to display a plurality of divided areas into which the preview image is divided, and obtains the position coordinates of the divided area selected by the user from among the plurality of divided areas as the position coordinates of the designated area. 3. The image processing apparatus according to claim 2, wherein: The display means is a touch panel,
3. The image processing apparatus according to claim 2, wherein said specifying means acquires position coordinates of an area drawn on said preview image by a user using said touch panel as the position coordinates of said specified area. The correcting means selects adjacent gradations in the order of magnitude of the first output gradation values associated with the input gradation values of the colors included in the object other than the object specified by the specifying means. 3. The first output gradation value is corrected to the second output gradation value so as to increase at least the smallest gradation value difference among gradation value differences between values. 7. The image processing device according to any one of 1 to 6. The correcting means selects adjacent gradations in the order of magnitude of the first output gradation values associated with the input gradation values of the colors included in the object other than the object specified by the specifying means. correcting the first output gradation value to the second output gradation value so that the gradation value difference is equal to or greater than the predetermined threshold when the gradation value difference between the values is less than the predetermined threshold; 7. The image processing apparatus according to any one of claims 1 to 6, characterized by: An image processing device that performs color conversion from color data to monochrome data,
The input gradation value of each color included in the color data is associated with the first output gradation value of each color in the monochrome data obtained by applying a conversion rule that maintains the reproducibility of each color. generating means for generating a conversion table;
Designating means for designating a specific color among the colors included in the color data based on a user input;
The first output gradation value of the conversion table is set to a second value so as to increase the discrimination in the monochrome data of colors included in the color data other than the color specified by the specifying means. a correction means for correcting the output gradation value;
conversion means for color-converting the color data according to the corrected conversion table;
An image processing device comprising: The specifying means causes the display means to display a button associated with a predetermined color included in the color data, and acquires the color associated with the button selected by the user as the specific color. 10. The image processing apparatus according to claim 9. The specifying means causes a display means to display a preview image of the color data, and acquires a color of a pixel on the preview image specified by the user as the specific color. 10. The image processing device according to Item 9. 10. The image processing apparatus according to claim 9, wherein said specifying means holds a color predetermined by a user, and reads said predetermined color as said specific color. The correcting means arranges the first output gradation values associated with the input gradation values excluding the color specified by the specifying means among the input gradation values so that adjacent gradations are arranged in order of magnitude. wherein the first output gradation value is corrected to the second output gradation value so as to increase at least the smallest gradation value difference among gradation value differences between the gradation values. Item 13. The image processing apparatus according to any one of Items 9 to 12. The correcting means arranges the first output gradation values associated with the input gradation values excluding the color specified by the specifying means among the input gradation values so that adjacent gradations are arranged in order of magnitude. correcting the first output gradation value to the second output gradation value so that the gradation value difference is equal to or greater than the predetermined threshold when the gradation value difference between the gradation values is less than the predetermined threshold; 13. The image processing apparatus according to any one of claims 9 to 12, wherein: In the first output gradation value, the correcting means increases at least the smallest gradation value difference between adjacent gradation values in the order of magnitude. 3. The first output gradation value associated with the input gradation value excluding the color specified by the specifying means among the gradation values is corrected to the second output gradation value. 13. The image processing apparatus according to any one of 9 to 12. When the gradation value difference between adjacent gradation values in the order of magnitude of the first output gradation values is less than a predetermined threshold value, the correction means determines that the gradation value difference is less than the predetermined threshold value. The first output gradation value associated with the input gradation value excluding the color specified by the specifying means is set to the second output gradation value so as to be equal to or greater than a threshold value. 13. The image processing apparatus according to any one of claims 9 to 12, wherein correction is performed. The correcting means is
gradation between adjacent gradation values in the order of magnitude of the first output gradation values associated with the input gradation value of the color specified by the specifying means among the input gradation values; correcting the first output gradation value to the second output gradation value so that the gradation value difference is greater than or equal to the predetermined threshold when the value difference is less than a predetermined threshold;
gradation between adjacent gradation values in the order of magnitude of the first output gradation values associated with the input gradation values excluding the color specified by the specifying means among the input gradation values; 13. The first output gradation value is corrected to the second output gradation value so as to increase at least the smallest gradation value difference among tone value differences. The image processing device according to any one of items 1 and 2. gradation between adjacent gradation values in the order of magnitude of the first output gradation values associated with the input gradation value of the color specified by the specifying means among the input gradation values; correcting the first output gradation value to the second output gradation value so that the gradation value difference is greater than or equal to the predetermined threshold when the value difference is less than a predetermined threshold;
The correcting means arranges the first output gradation values associated with the input gradation values excluding the color specified by the specifying means among the input gradation values so that adjacent gradations are arranged in order of magnitude. correcting the first output gradation value to the second output gradation value so that the gradation value difference is equal to or greater than the predetermined threshold when the gradation value difference between the gradation values is less than the predetermined threshold; 13. The image processing apparatus according to any one of claims 9 to 12, wherein: An image processing method for color conversion from color data to monochrome data,
The input gradation value of each color included in the color data is associated with the first output gradation value of each color in the monochrome data obtained by applying a conversion rule that maintains the reproducibility of each color. generating a conversion table;
designating a specific object among the objects included in the color data based on user input;
The first output gradation value of the conversion table is set to a second value so as to increase the discrimination in the monochrome data of the objects included in the color data other than the object specified in the specifying step. a step of correcting to the output tone value of
color-converting the color of the designated object according to the conversion table before correction, and converting the color of the object other than the designated object according to the conversion table after correction;
An image processing method comprising: An image processing method for color conversion from color data to monochrome data,
The input gradation value of each color included in the color data is associated with the first output gradation value of each color in the monochrome data obtained by applying a conversion rule that maintains the reproducibility of each color. generating a conversion table;
Designating a specific color among the colors included in the color data based on user input;
The first output gradation value of the conversion table is set to a second value so as to enhance the discrimination in the monochrome data of the colors included in the color data other than the color specified in the specifying step. a step of correcting to the output tone value of
a step of color-converting the color data according to the corrected conversion table;
An image processing method comprising: A program for causing a computer to function as the image processing apparatus according to any one of claims 1 to 16.

Images