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WO2018187989A1 - Procédé et appareil de détection utilisables avec un écran d'affichage - Google Patents

Procédé et appareil de détection utilisables avec un écran d'affichage Download PDF

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Publication number
WO2018187989A1
WO2018187989A1 PCT/CN2017/080284 CN2017080284W WO2018187989A1 WO 2018187989 A1 WO2018187989 A1 WO 2018187989A1 CN 2017080284 W CN2017080284 W CN 2017080284W WO 2018187989 A1 WO2018187989 A1 WO 2018187989A1
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WO
WIPO (PCT)
Prior art keywords
value
display screen
image
test item
differential
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Ceased
Application number
PCT/CN2017/080284
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English (en)
Chinese (zh)
Inventor
陈灿
黄柏翰
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EELY Guangzhou Electronic Technology Co Ltd
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EELY Guangzhou Electronic Technology Co Ltd
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Priority to PCT/CN2017/080284 priority Critical patent/WO2018187989A1/fr
Priority to CN201780021454.9A priority patent/CN108885180B/zh
Publication of WO2018187989A1 publication Critical patent/WO2018187989A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells

Definitions

  • Embodiments of the present invention relate to the field of electronic device screen detection technologies, and in particular, to a display screen detection method and apparatus.
  • the current practice is that workers control electronic devices to play a variety of photos, such as solid-colored photos, landscape photos, and portrait photos, which are evaluated by visually observing the display of the screen. Manually detecting the screen of an electronic device is not only inefficient, but also the accuracy of the inspection is affected by individual differences.
  • Embodiments of the present invention provide a method and apparatus for detecting a display screen to improve the efficiency of detecting a display screen.
  • an embodiment of the present invention provides a method for detecting a display screen, where the method includes:
  • the result of the at least one test item is determined by using a fuzzy logic decision method, and the detection result of the display screen to be tested is obtained.
  • the adjusting the camera sensitivity value according to the preset brightness value adaptively includes:
  • the third light sensitivity value is a camera light sensitivity value.
  • the method further includes:
  • the calculating a degree of change of each image point of the plurality of acquired images in the spatial domain to obtain a differential image of the acquired image includes:
  • At least one data reflecting the brightness of the image point is separately calculated as a partial differential in two mutually perpendicular directions, and a partial differential value of the at least one data is a degree of change of the image point.
  • the detecting of the at least one test item in the differential map of the plurality of acquired images comprises:
  • At least one test item is detected for an image point whose partial differential value is not equal to zero.
  • the fuzzy logic determination method is used to judge the result of the at least one test item shown And obtaining the detection result of the display screen to be tested, including:
  • an embodiment of the present invention further provides a detection device for a display screen, the device comprising:
  • a camera sensation adjustment module configured to set a brightness of the display to be tested to a preset brightness value, and adaptively adjust a camera sensation value according to the preset brightness value;
  • An image acquisition module configured to collect a picture displayed on the display screen according to the camera sensitivity value, and obtain a plurality of acquired images
  • a differential map obtaining module configured to calculate a degree of change of each image point of the plurality of acquired images in a spatial domain, to obtain a differential map of the acquired image
  • test item detecting module configured to perform at least one test item detection in the differential map of the plurality of acquired images
  • a detection result obtaining module configured to determine, by using a fuzzy logic determination method, a result of the at least one verification item, and obtain a detection result of the display screen to be tested.
  • the camera sensitization value adjustment module is further configured to:
  • the third light sensitivity value is a camera light sensitivity value.
  • a moiré filtering module for filtering moiré in the plurality of captured images.
  • differential map obtaining module is further configured to:
  • At least one data reflecting the brightness of the image point is separately calculated as a partial differential in two mutually perpendicular directions, and a partial differential value of the at least one data is a degree of change of the image point.
  • differential map obtaining module is further configured to:
  • At least one test item is detected for an image point whose partial differential value is not equal to zero.
  • the detection result obtaining module is further configured to:
  • the brightness of the display screen to be tested is set to a preset brightness value, and the camera sensitivity value is adaptively adjusted according to the preset brightness value, and then the picture displayed on the display screen is collected according to the camera sensitivity value, and more is obtained.
  • the image is acquired, and then the degree of change of each image point of the plurality of acquired images in the spatial domain is calculated, and a differential image of the acquired image is obtained, and then at least one test item is detected in the differential map of the plurality of acquired images, and finally
  • the fuzzy logic determination method is used to determine the result of at least one test item, and the detection result of the display screen to be tested is obtained.
  • FIG. 1 is a flowchart of a method for detecting a display screen according to Embodiment 1 of the present invention
  • FIG. 2 is a flowchart of a method for detecting a display screen according to Embodiment 2 of the present invention
  • FIG. 3 is a flowchart of a method for detecting a display screen according to Embodiment 3 of the present invention.
  • FIG. 4 is a schematic structural diagram of a detecting device for a display screen according to Embodiment 4 of the present invention.
  • FIG. 1 is a flowchart of a method for detecting a display screen according to a first embodiment of the present invention.
  • the embodiment can be applied to the display effect detection on a display screen, wherein the display screen can be a liquid crystal display (LCD). ), Light Emitting Diode (LED), Organic Light Emitting Diode (OLED), Cathode Ray Tube (CRT) display, Plasma Display Panel (PDP) ), and any display screen that can change the display image according to the signal.
  • the method specifically includes the following steps:
  • Step 110 Set the brightness of the display to be tested to a preset brightness value, and adaptively adjust the camera sensitivity value according to the preset brightness value.
  • the preset brightness value may be a maximum brightness percentage displayed on the display screen to be tested, and may be set to any value between 70% and 90%.
  • the camera sensitivity value can be the camera's analog gain or exposure time. In this embodiment, when the display effect of the display screen is detected, the image displayed on the detection display screen is required to be photographed, and in order to obtain a better image, the sensitivity value of the camera needs to be adjusted.
  • the method of adaptively adjusting the camera sensitization value according to the preset brightness value may be: defining a first sensible value and a second sensible value when the camera collects an image, wherein the first sensible value is greater than the second sensible value, The first photosensitive value and the second photosensitive value are averaged to obtain a third photosensitive value. Light up the display to be tested, so that the display screen displays a white screen, and the screen brightness is the maximum brightness. The third sensitivity value is used to collect the picture, and the average brightness of the picture is calculated. If the difference between the average brightness and the preset brightness value is less than the preset error value , the third sensitivity value is the camera sensitivity value.
  • the difference between the average brightness and the preset brightness value is greater than a preset error value, and the average brightness is less than the preset brightness value. Then, the second sensitization value is reset to the current camera sensation value, and then the third sensation value is obtained, and the third sensible value obtained by re-taking is taken, and the average brightness of the picture is calculated, and the average brightness and the preset brightness value are calculated. The difference is compared to the preset error value. The adjustment is performed a plurality of times until the difference between the average brightness and the preset brightness value is less than the preset error value.
  • the difference between the average brightness and the preset brightness value is greater than a preset error value, and the average brightness is greater than the preset brightness value. Then, the first sensitized value is reset to the current camera sensitization value, and then the third sensible value is obtained, and the third sensible value obtained by re-photographing is taken, and the average brightness of the picture is calculated, and the average brightness and the preset brightness value are calculated. The difference is compared to the preset error value. The adjustment is performed a plurality of times until the difference between the average brightness and the preset brightness value is less than the preset error value.
  • Step 120 Collecting a picture displayed on the display screen according to the camera sensitivities, and obtaining a plurality of acquired images.
  • the captured image may be a color image displayed on the display screen to be tested, and may include a white image, a black image, a gray image, a red image, a green image, and a blue image.
  • the cameras of different colors displayed on the display screen are respectively photographed by using the camera with the adjusted sensitivity value, and multiple images are acquired.
  • Step 130 Calculate a degree of change of each image point of the plurality of acquired images in the spatial domain to obtain a differential image of the acquired image.
  • the degree of change of the image point may be the degree of change in brightness of the pixel of the image.
  • the manner of calculating the degree of change of each image point of the plurality of acquired images in the spatial domain may be: for a plurality of images of different colors, respectively, at least one data reflecting the brightness of the image points along two mutual The vertical direction is calculated separately for the partial differential, and the partial differential value of at least one of the data is the degree of change of the image point.
  • two mutually perpendicular directions may form a Cartesian coordinate system, and each pixel point has a corresponding position coordinate (x, y) in the teaching coordinate system.
  • the luminance values on the pixel position (x, y) coordinates of the image are in one-to-one correspondence with the coordinates (x, y, z) of the Euclidean three-dimensional space.
  • the difference between the brightness value of a certain pixel point and the brightness value of the surrounding pixel points is the brightness change value of the pixel point, which can be obtained by obtaining partial differential.
  • the pixel points represent the brightness data, and the degree of brightness change of each pixel point in two directions can be obtained by the partial differential algorithm.
  • the image data is embodied in red, green and blue (RGB) format, which respectively reflects red luminance data, green luminance data and blue luminance data.
  • the partial differential algorithm can obtain the brightness variation of the corresponding color of each pixel.
  • Step 140 Perform detection of at least one test item in a differential map of the plurality of acquired images.
  • the test items may include black and white group inspection, stain inspection, bright spot inspection, bright spot inspection, bright dark spot inspection, light leakage inspection, light shadow inspection and yellowish inspection.
  • the display screen is a perfect screen, and for the qualified screen, the differential value of the pixel in the screen to be tested is satisfied.
  • the method for performing the detection of the at least one test item in the differential map of the plurality of acquired images may be: searching for an image point whose partial differential value is not equal to 0, and performing at least one test item for the image point whose partial differential value is not equal to 0. Inspection Measurement.
  • the black and white group may be: in the differential graph, the differential value is greater than 0 and the inner non-hole region is the white group at the corresponding position, and the differential value in the differential map is less than 0 and the inner non-hole region is the black group at the corresponding position.
  • the smear may be a closed region in the differential map having a differential value greater than zero (or a differential value less than zero) and having a hole inside.
  • the bright spot can be a lone point with a differential value greater than zero in the differential map.
  • a bright spot may be a closed region in a differential map having a differential value greater than zero and having multiple internal holes.
  • the bright dark spot may be a closed area in which the differential value is greater than 0 in the differential image and the inner edge has a certain thickness of the edge, and the closed area in the corresponding position is a bright spot in the corresponding position, and the differential value in the differential image is less than 0 and the inner closed portion has a certain thickness of the closed area. It is a dark spot on the corresponding position.
  • the light leakage may be an area in which the differential value in the differential map is greater than 0 (or less than 0) and there is no hole inside and the difference between the shape shape and the shape closure area ratio is 0.5 to 2.
  • the light shadow may be a region in which the differential value in the differential map is greater than 0 (or less than 0) and there is no hole inside and the difference between the shape shape and the shape closure area ratio is less than 0.5 or greater than 2.
  • the yellowish picture may be yellowish in the mean color of the white and gray images in the spatial domain image.
  • the inspection items for detecting the white image include a black and white group inspection, a stain inspection, a light shadow inspection, and a screen whitening inspection.
  • Test items for detecting black images include bright spot test, bright spot test, and light leak test.
  • the test items for detecting gray image, red image, green image and blue image are all bright dark spot test. In this application scenario, when detecting the display effect of each display to be tested, six different color images are to be inspected.
  • Step 150 Determine a result of the at least one test item by using a fuzzy logic determination method, and obtain a detection result of the display screen to be tested.
  • the fuzzy logic judgment method can be a reasoning thinking system with transition between the true and the false and the true and false as the basic conceptual elements.
  • the detection result of each test item is not only represented by OK and NG, but a value indicating the test result of each test item is represented by a numerical value.
  • the degree value for example, the value of the degree of inspection detected by the test item is represented by 0-100 points.
  • the smudge test is taken as an example, 0 means no smudge on the display screen, and 100 means smudged on the display screen. , 20 indicates that there is a possibility of smudging on the display screen of 50%, and 80 indicates that the possibility of smudge on the display screen is 80%.
  • the fuzzy logic determination method is used to determine the result of at least one test item, and the method for obtaining the test result of the display screen to be tested may be: comparing the result of the test item with the fuzzy logic standard value of the test item, if If the result of the test item is greater than the fuzzy logic standard value of the test item, the inspection result of the display screen to be tested is unqualified. If the result of the test item is less than or equal to the fuzzy logic standard value of the test item, the inspection result of the display screen to be tested is qualified. .
  • the stain test as an example, if the fuzzy logic standard value of the stain is set to 30, and the stain value of the product A is 60, the product A is not qualified in the stain inspection, and the product B is detected. In the result, the stain value was 20, and the product B was qualified in the stain test. In this embodiment, when the inspection items in the images of the six different colors of the product are detected, all the inspection items are required to pass, and the product is qualified.
  • the fuzzy logic determination method is used to determine the result of the at least one test item, and may further include: when the test item detection result of a product is unqualified, and the detection result is close to the data in the machine learning library, then the The product can be specially qualified.
  • the product of the fuzzy logic setting value of product A, debris 10, bright spot 35, and color cast 50 is determined to be unacceptable. However, if the customer and supplier of this type of product agree to be qualified, the machine learning library will enter the test result value of the product and save the product image.
  • the machine This product was identified as qualified according to the recorded learning data.
  • the method further includes:
  • step 160 the moiré in the plurality of captured images is filtered out.
  • the moiré is a pixel point whose frequency in the frequency domain is greater than a preset frequency.
  • Images in which the human eye can acquire image intentional information are all spatial domain based images. For example, in a photo, the object in the photo appears on the photo according to the relative position of the space and the relative brightness color of the position, and the human eye recognizes the intentional information of the image by the brightness color embodied by the spatial position of the object in the photo.
  • Images that are directly recognized by the human eye and the visual system are spatial domain-based images. Compared with spatial domain-based images, there are frequency domain-based or time-domain-based images. Even if such images contain the same image information as the spatial domain-based images, they cannot be directly recognized by the human eye and the visual system. The information contained in it.
  • the method for filtering out the moiré in the plurality of acquired images may be: first, transforming the image in the spatial domain into a frequency domain by using a Fourier transform, and then using the frequency in the frequency domain to be greater than the preset frequency.
  • the pixel points are deleted, and finally the frequency domain map image is converted back to the spatial domain by using an inverse Fourier transform.
  • the moiré on the image of the spatial domain is filtered out.
  • the Fourier transform and the inverse Fourier transform method are used to filter out the moiré in the image, which can eliminate the interference of the moiré on the image.
  • the technical solution of the embodiment firstly sets the brightness of the display screen to be tested to a preset brightness value, adaptively adjusts the camera sensitivity value according to the preset brightness value, and then collects the picture displayed on the display screen according to the camera sensitivity value. Obtaining a plurality of acquired images, and then calculating a degree of change of each image point of the plurality of acquired images in the spatial domain, obtaining a differential image of the acquired image, and then performing at least one test item detection in the differential map of the plurality of acquired images Finally, the fuzzy logic determination method is used to determine the result of at least one test item, and the detection result of the display screen to be tested is obtained.
  • the technical solution provided by the embodiment of the invention overcomes the problem of low efficiency when manually detecting the screen in the prior art, and improves the efficiency of detecting the display effect of the electronic device to be detected.
  • FIG. 2 is a flowchart of a method for detecting a display screen according to Embodiment 2 of the present invention. Based on the foregoing embodiment, as shown in FIG. 2, step 110 includes:
  • Step 111 Define a first sensible value and a second sensible value when the camera captures an image, wherein the first sensible value is greater than the second sensible value.
  • the first sensitization value may be a maximum analog gain or a longest exposure time when the camera takes a picture, and is referred to as a maximum camera sensation value.
  • the second sensitization value may be the minimum analog gain or the shortest exposure time when the camera takes a picture, which is called the minimum camera sensation value.
  • Step 112 averaging the first photosensitive value and the second photosensitive value to obtain a third photosensitive value.
  • the first sensitized value and the second sensible value of the camera are added and divided by two to obtain a third sensitized value.
  • Step 113 Acquire a picture by using the third photosensitive value, and calculate an average brightness of the picture.
  • Step 114 If the difference between the average brightness and the preset brightness value is less than the preset error value, the third light sensitivity value is the camera light sensing value.
  • the preset error value can be set to any value between 0-10% of the maximum brightness of the display.
  • the maximum brightness of the display screen is 300, and the preset error value can be set to any number between 0-30.
  • the photosensitive value of the camera is set to the third sensitivity value.
  • the difference between the average brightness and the preset brightness value is greater than a preset error value, and the average brightness is less than the preset brightness value. Then, the second sensitization value is reset to the current camera sensation value, and then the third sensation value is obtained, and the third sensible value obtained by re-taking is taken, and the average brightness of the picture is calculated, and the average brightness and the preset brightness value are calculated. The difference is compared to the preset error value. Adjusting so many times until the average brightness is the same as the pre- Let the difference between the brightness values be less than the preset error value.
  • the difference between the average brightness and the preset brightness value is greater than a preset error value, and the average brightness is greater than the preset brightness value. Then, the first sensitized value is reset to the current camera sensitization value, and then the third sensible value is obtained, and the third sensible value obtained by re-photographing is taken, and the average brightness of the picture is calculated, and the average brightness and the preset brightness value are calculated. The difference is compared to the preset error value. The adjustment is performed a plurality of times until the difference between the average brightness and the preset brightness value is less than the preset error value.
  • the camera's first photosensitive value and the second photosensitive value are adaptively adjusted to adjust the camera's light sensitivity value, so that the camera can capture the image of the display screen.
  • FIG. 3 is a flowchart of a method for detecting a display screen according to Embodiment 3 of the present invention. Based on the foregoing embodiment, as shown in FIG. 3, preferably, step 150 includes:
  • step 151 the result of the test item is compared with the fuzzy logic standard value of the test item.
  • the fuzzy logic standard value can be set according to the characteristics of the product and the needs of the customer.
  • Step 152 if the result of the test item is greater than the fuzzy logic standard value of the test item, the check result of the display screen to be tested is unqualified.
  • each color corresponds to a different inspection item, and if one of the inspection items fails, the display to be tested is unqualified. That is, when all the inspection items are qualified, the display to be tested is qualified.
  • the detection method of the display screen of this embodiment is based on concurrent calculation of multi-core multi-thread.
  • single-core multi-thread scheduling method since only one central processing unit (CPU) can execute one instruction at a time, single-core multi-thread scheduling is implemented based on time slice segmentation. Single core CPU Only one thread can be executed at the same time, and other threads are in a sleep state.
  • An algorithm is divided into two implementations, which implements A as a single-threaded operation and B as a multi-threaded operation.
  • implementation A When implementation A is executed on a single-core CPU, if the time required to implement A's thread CPU usage reaches 100% is Ta, then the time to implement B on the single-core CPU is Ta+Tt*N, N>> 0. It can be concluded that the implementation of implementation A on a single-core CPU is less than the time to implement implementation B, that is, single-thread execution is the fastest method when executing an algorithm on a single-core CPU.
  • the CPU has M cores and can execute M instructions at the same time. Therefore, the multi-core multi-thread scheduling is implemented based on the priority CPU core segmentation and then the time slice segmentation.
  • each CPU core is allocated to execute one thread, and the redundant CPU core is idle. If the number of threads to be executed is greater than M, one thread is preferentially allocated to each CPU core, and the redundant threads are scheduled for time slice segmentation on the most idle CPU core.
  • the most idle CPU core may change after each scheduling. So the extra threads are not necessarily executed on one of the most idle CPU cores, but are distributed to several of the most idle CPU cores at the time.
  • the algorithm is divided into two implementations, which implements A as a single-threaded operation and B as a multi-threaded operation (the number of threads is N).
  • FIG. 4 is a schematic structural diagram of a display device for a display screen according to Embodiment 4 of the present invention. As shown in FIG. 4, the device includes: a camera sensitivity adjustment module 410, an image acquisition module 420, and a differential image acquisition. The module 430, the verification item detection module 440 and the detection result acquisition module 450 are taken.
  • the camera sensation value adjustment module 410 is configured to set the brightness of the display screen to be tested to a preset brightness value, and adaptively adjust the camera sensation value according to the preset brightness value;
  • the image acquisition module 420 is configured to collect a picture displayed on the display screen according to the camera sensitivity value, and obtain a plurality of acquired images;
  • a differential map obtaining module 430 configured to calculate a degree of change of each image point of the plurality of acquired images in the spatial domain, to obtain a differential map of the acquired image
  • the test item detecting module 440 is configured to perform detection of at least one test item in the differential map of the plurality of acquired images
  • the detection result obtaining module 450 is configured to determine the result of the at least one test item by using the fuzzy logic determination method, and obtain the detection result of the display screen to be tested.
  • the camera sensitivity adjustment module 410 is further configured to:
  • the third light sensitivity value is the camera light sensitivity value.
  • the method further includes:
  • Moiré filter module for filtering moiré in multiple captured images.
  • the differential map obtaining module 430 is further configured to:
  • the partial differential value of at least one data is the degree of change of the image point.
  • the differential map obtaining module 430 is further configured to:
  • At least one test item is detected for an image point whose partial differential value is not equal to zero.
  • the detection result obtaining module 450 is further configured to:
  • the above product can perform the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

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Abstract

L'invention concerne un procédé et un appareil de détection utilisables avec un écran d'affichage. Le procédé consiste: à configurer la luminosité d'un écran d'affichage à détecter en tant que valeur de luminosité prédéfinie, et à ajuster de manière auto-adaptative une valeur de détection de lumière d'une caméra en fonction de la valeur de luminosité prédéfinie; à recueillir, en fonction de la valeur de détection de lumière de la caméra, des images présentées sur l'écran d'affichage à détecter pour obtenir une pluralité d'images recueillies; à calculer un degré de variation pour chaque point d'image de la pluralité d'images recueillies dans le domaine spatial pour obtenir un graphe différentiel des images recueillies; à détecter au moins un élément de détection dans le diagramme différentiel de la pluralité d'images recueillies; à effectuer une détermination sur un résultat d'au moins un élément de détection au moyen d'un procédé de détermination de logique floue pour obtenir un résultat de détection pour l'écran d'affichage à détecter. Le procédé de détection résout le problème d'efficacité faible de la technologie actuelle lorsqu'on effectue manuellement une détection sur un écran, et augmente l'efficacité de détection de l'effet d'affichage d'un dispositif électronique à détecter.
PCT/CN2017/080284 2017-04-12 2017-04-12 Procédé et appareil de détection utilisables avec un écran d'affichage Ceased WO2018187989A1 (fr)

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PCT/CN2017/080284 WO2018187989A1 (fr) 2017-04-12 2017-04-12 Procédé et appareil de détection utilisables avec un écran d'affichage
CN201780021454.9A CN108885180B (zh) 2017-04-12 2017-04-12 一种显示屏的检测方法及装置

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CN113014908A (zh) * 2019-12-19 2021-06-22 西安诺瓦星云科技股份有限公司 图像检测方法、装置和系统及计算机可读存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011086634A1 (fr) * 2010-01-14 2011-07-21 シャープ株式会社 Procédé d'inspection d'un écran à cristaux liquides et dispositif
CN102692418A (zh) * 2012-06-13 2012-09-26 北京优纳科技有限公司 一种平板显示屏的外观及功能检测设备及检测方法
US20140198202A1 (en) * 2013-01-14 2014-07-17 Samsung Display Co., Ltd. Inspection method for display panel
CN106153639A (zh) * 2015-04-21 2016-11-23 凯吉凯精密电子技术开发（苏州）有限公司 基于人工智能的电路板检测方法及其检测装置
CN106442560A (zh) * 2016-08-23 2017-02-22 汕头大学 一种显示屏的定位测量与缺陷检测方法

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004361358A (ja) * 2003-06-09 2004-12-24 Hitachi Kokusai Electric Inc ディスプレイ装置の欠陥検査装置
JP4143660B2 (ja) * 2006-07-13 2008-09-03 シャープ株式会社 画像解析方法、画像解析装置、検査装置、画像解析プログラムおよびコンピュータ読み取り可能な記録媒体
JP4799329B2 (ja) * 2006-09-07 2011-10-26 株式会社東芝 ムラ検査方法、表示パネルの製造方法及びムラ検査装置
KR100891842B1 (ko) * 2007-08-28 2009-04-07 주식회사 포스코 원형 선재 광학결함 검출장치 및 방법
JP4726983B2 (ja) * 2009-10-30 2011-07-20 住友化学株式会社 欠陥検査システム、並びに、それに用いる、欠陥検査用撮影装置、欠陥検査用画像処理装置、欠陥検査用画像処理プログラム、記録媒体、および欠陥検査用画像処理方法
CN102404495B (zh) * 2010-09-10 2014-03-12 华晶科技股份有限公司 数字相机的拍摄参数的调整方法
CN103106859B (zh) * 2013-02-28 2015-11-25 北京星河康帝思科技开发股份有限公司 显示屏的检测方法和装置
CN104698616A (zh) * 2013-12-06 2015-06-10 大连龙宁科技有限公司 基于模糊逻辑的液晶显示屏透光度快速检测方法
CN104038703A (zh) * 2014-05-26 2014-09-10 四川长虹电器股份有限公司 数字摄像机感光自适应控制方法
CN105575366B (zh) * 2016-02-26 2017-10-24 广东欧珀移动通信有限公司 切换背光调节速度的方法及系统
CN105976382B (zh) * 2016-05-11 2018-11-13 华中科技大学 一种基于缺陷区预判和水平集的TFT-LCD Mura缺陷检测方法
CN107705290B (zh) * 2017-09-05 2021-07-02 哈尔滨工业大学深圳研究生院 一种AMOLED显示屏Mura缺陷检测方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011086634A1 (fr) * 2010-01-14 2011-07-21 シャープ株式会社 Procédé d'inspection d'un écran à cristaux liquides et dispositif
CN102692418A (zh) * 2012-06-13 2012-09-26 北京优纳科技有限公司 一种平板显示屏的外观及功能检测设备及检测方法
US20140198202A1 (en) * 2013-01-14 2014-07-17 Samsung Display Co., Ltd. Inspection method for display panel
CN106153639A (zh) * 2015-04-21 2016-11-23 凯吉凯精密电子技术开发（苏州）有限公司 基于人工智能的电路板检测方法及其检测装置
CN106442560A (zh) * 2016-08-23 2017-02-22 汕头大学 一种显示屏的定位测量与缺陷检测方法

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BAI, XIAOJING: "RESEARCH on IMAGE SEGMENTATION and REGISTRATION BASED on PARTIAL DIFFERENTIAL EQUATIONS", CHINA DOCTORAL DISSERTATIONS FULL-TEXT DATABASE, 15 August 2010 (2010-08-15), pages 1, ISSN: 1674-022X *
ZGANG, YU: "RESEARCH on MURA INSPECTION TECHNOLOGY of TDT-LCD BASED on MACHINE VISION", CHINA DOCTORAL DISSERTATIONS FULL-TEXT DATABASE, 15 November 2006 (2006-11-15), pages 94 - 98, ISSN: 1671-6779 *

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