Display Defect Detection Method and Device

Abstract

The present invention relates to the field of display technologies, and discloses a display screen display defect detection method and device. Among them, the display screen display defect detection method includes: obtaining a sampled image, where the sampled image is an image obtained by photographing a display screen displaying a sample image; obtaining each pixel point in the sampled image; performing brightness noise removal processing on each pixel point respectively to obtain a target image; performing defect detection on the target image to obtain the defect positions in the target image; where the brightness noise removal processing includes: calculating the ambient light brightness value at the pixel point, where the ambient light brightness value is the brightness value of the ambient light outside the display screen at the pixel point, and performing brightness compensation on the brightness of the pixel point according to the ambient light brightness value. Compared with the prior art, the display screen display defect detection method and device provided by the embodiments of the present invention have the advantage of improving the accuracy of display screen defect detection.

Description

Technical Field

[0001] The present invention relates to the field of display technologies, and particularly to a method and device for detecting display defects of a display screen. Background Art

[0002] During the production process of a display screen, due to reasons such as materials, processes, and structures, some products may have the phenomenon of uneven display brightness of the picture; such uneven brightness spot traces will bring discomfort to the vision, and products with such Mura traces cannot meet the specifications of end customers. For example, in a foldable display screen, due to the presence of creases in the bending area and the unevenness of the film layer and the adhesive layer, it will cause a visual impact on the human eye and cause Mura defects in the bending area. For the Mura defects of uneven display brightness of the display screen, in the prior art, an external compensation system is used to eliminate the Mura pattern of the display screen with Mura defects through sub-pixel level optical imaging technology and software algorithms, so that the display quality of the display screen meets the shipping specifications of the panel factory and improves the yield of mass production of the display screen. The premise of performing brightness compensation on the Mura area is to accurately detect the Mura area of the display screen.

[0003] However, the inventors of the present invention have found that the defect detection effect of the display defect detection method in the prior art is poor, and the detection result of the Mura area is inaccurate, resulting in a poor display result after brightness compensation. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a method and device for detecting display defects of a display screen, so as to improve the accuracy of detecting display screen defects.

[0005] To solve the above technical problems, an embodiment of the present invention provides a method for detecting display defects of a display screen, which is used to detect a display screen displaying a sample image, and includes: obtaining a sampled image, where the sampled image is an image obtained by photographing the display screen displaying the sample image; obtaining each pixel point in the sampled image; performing brightness impurity removal processing on each pixel point respectively to obtain a target image; performing defect detection on the target image to obtain the defect positions in the target image; where the brightness impurity removal processing includes: calculating the ambient light brightness value at the pixel point, where the ambient light brightness value is the brightness value of the ambient light outside the display screen at the pixel point, and performing brightness compensation on the brightness of the pixel point according to the ambient light brightness value.

[0006] Embodiments of the present invention also provide a display screen display defect detection device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the display screen display defect detection method as described above.

[0007] Compared with the prior art, in the embodiments of the present invention, after obtaining a sampled image by photographing a display screen showing a sample image, before performing defect detection on the sampled image, brightness impurity removal processing is also performed on each pixel point in the sampled image, and the brightness of the pixel point is compensated by calculating the ambient light brightness value at the pixel point, so as to remove the influence of ambient light on the brightness value of the pixel point, and a target image with the influence of ambient light on brightness removed is obtained. Performing defect detection on the target image can avoid the influence of ambient light on the defect detection result and improve the accuracy of the defect detection result.

[0008] Preferably, calculating the ambient light brightness value at the pixel point specifically includes: obtaining other pixel points within a preset range around the pixel point to obtain a plurality of target pixel points; calculating the average brightness of at least some of the target pixel points as the ambient light brightness value at the pixel point.

[0009] Preferably, calculating the average brightness of at least some of the target pixel points specifically includes: sorting the target pixel points in descending order of brightness; calculating the average brightness of the target pixel points ranked in the top N positions as the ambient light brightness value, where N is a positive integer greater than 1.

[0010] Preferably, before calculating the average brightness of the target pixel points ranked in the top N positions, it further includes: excluding the target pixel point ranked first; re-sorting the remaining target pixel points in descending order of brightness.

[0011] Preferably, compensating the brightness of the pixel point according to the ambient light brightness value specifically includes: obtaining the brightness of the pixel point in the sampled image as the pixel brightness value; determining whether the ambient light brightness value corresponding to the pixel point is greater than the pixel brightness value corresponding to it; if not, outputting a compensation brightness value of 255; if so, outputting a compensation brightness value of 255 - (A - B), where A is the background brightness value and B is the pixel brightness value; replacing the pixel brightness value of the pixel point with the compensation brightness value.

[0012] Preferably, before replacing the pixel brightness value of the pixel point with the compensation brightness value after the output compensation brightness value is 255 - (A - B), it further includes: determining a contrast expansion coefficient k according to the pixel brightness value, and changing the compensation brightness value to 255 - k*(A - B).

[0013] Preferably, the determining the contrast expansion coefficient k according to the pixel brightness value specifically includes: according to the formula

[0014] determining the contrast expansion coefficient k; where B1 and B2 are preset constants, and I b (x, y) is the pixel brightness value of the pixel point.

[0015] Preferably, before replacing the pixel brightness value of the pixel point with the compensation brightness value after changing the compensation brightness value to 255 - k*(A - B), it further includes: judging whether 255 - k*(A - B) is less than 191; if so, changing the compensation brightness value to 191.

[0016] Preferably, the performing defect detection on the target image specifically includes: performing binarization processing on the target image, and performing defect detection on the binarized target image.

[0017] Preferably, the performing defect detection on the binarized target image specifically includes: calculating the average value of the brightness of each pixel point in the binarized target image; taking the pixel points with brightness less than the average value as the pixel points with display defects. Description of the Drawings

[0018] Figure 1 is a flowchart of the method for detecting display defects of a display screen provided by the first embodiment of the present invention;

[0019] Figure 2 is a flowchart of the process of performing brightness impurity removal processing on each pixel point respectively in the method for detecting display defects of a display screen provided by the first embodiment of the present invention;

[0020] Figure 3 is a flowchart of the process of calculating the ambient light brightness value at a pixel point in the method for detecting display defects of a display screen provided by the first embodiment of the present invention;

[0021] Figure 4 is a flowchart of the process of obtaining some target pixel points from multiple target pixel points in the method for detecting display defects of a display screen provided by the first embodiment of the present invention;

[0022] Figure 5It is a schematic diagram of a process of performing brightness compensation on the brightness of a pixel point according to the brightness value of ambient light in the display screen display defect detection method provided by the first embodiment of the present invention;

[0023] Figure 6 is a schematic flow chart of a display screen display defect detection method provided by a second embodiment of the present invention;

[0024] Figure 7 It is a schematic structural diagram of a display screen display defect detection device provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the present invention clearer, the following will be described in detail with reference to the accompanying drawings. However, it will be appreciated by those skilled in the art that in the various embodiments of the present invention, many technical details are provided in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented.

[0026] The invention of the present invention finds that the OLED display screen in the prior art may have a mura defect of uneven brightness display during the display process due to the influence of the manufacturing process or the structure of the display screen, and a method for removing the mura defect is to shoot an image of a sample screen displayed on the display screen, perform defect detection on the shot image, obtain the area with the mura defect and the brightness data of the defective area, and perform brightness compensation on the defective area during display according to the position and brightness data of the defective area, so as to remove the display defect of uneven brightness display. However, when shooting the image of the sample screen displayed on the display screen, due to the influence of ambient lighting, shooting angle, etc., the shot image and the image displayed on the display screen are not exactly the same, and when the image shot under the influence of ambient lighting is subjected to defect detection, the ambient lighting will affect the defect detection result, thereby reducing the accuracy of the defect detection result.

[0027] In order to solve the above technical problems, the first embodiment of the present invention relates to a display screen display defect detection method for detecting a display screen displaying a sample image. The specific process is as follows: Figure 1 As shown, including:

[0028] Step S101: acquiring a sample image, where the sample image is an image obtained by photographing a display screen displaying a sample image.

[0029] Specifically, in this step, a sample image is first displayed on the display screen to be tested, and a camera device such as a CCD camera or a digital camera is used to photograph the display screen displaying the sample image, and the image obtained by the photographing is used as the sampling image.

[0030] In this embodiment, after the display screen is lit, due to the different display requirements of display screens of different brands and types, the pictures to be detected are also different. Commonly, there are RGB images with 32, 64, 96, 160, 192, and 224 gray levels, a total of 18 pictures. That is, 18 sampling images with different gray levels are obtained and defect detection is performed separately. It can be understood that the foregoing obtaining 18 sampling images with different gray levels and performing defect detection separately is only a specific example in this embodiment and does not constitute a limitation. In other embodiments of the present invention, sampling images can also be collected according to other criteria, and specific settings can be flexibly made according to actual needs. In addition, in this embodiment, the steps of performing defect detection on sampling images with different gray levels are carried out separately, that is, the following defect detection steps are carried out for each sampling image separately. The following sampling image is any one of multiple sampling images, rather than performing defect detection on all sampling images simultaneously.

[0031] Step S102: Obtain each pixel point in the sampling image.

[0032] Specifically, in this step, it can be to directly obtain the division of each pixel point in the sampling image when the sampling image is captured by the imaging device, or to divide each pixel point in the sampling image through image processing technology after obtaining the sampling image. Specific settings can be flexibly made according to actual needs.

[0033] Step S103: Perform brightness impurity removal processing on each pixel point respectively to obtain a target image.

[0034] Specifically, in this step, when performing brightness impurity removal processing on each pixel point respectively, the processes of performing brightness impurity removal processing between each pixel point are independent of each other and can be carried out simultaneously or one by one in sequence. Specific settings can be flexibly made according to actual needs. The steps of specifically performing brightness impurity removal processing on any one pixel point are as Figure 2 shown and include:

[0035] Step S201: Calculate the ambient light brightness value at the pixel point.

[0036] Specifically, in this step, the ambient light brightness value is the brightness value of the ambient light outside the display screen at the pixel point. The specific calculation method is as Figure 3 shown and includes:

[0037] Step S301: Obtain other pixel points within a preset range around the pixel point to obtain a plurality of target pixel points.

[0038] Specifically, in this step, for example, pixel points within a circular area centered on this pixel point with a radius of r are obtained as target pixel points, or pixel points within a rhombus area centered on this pixel point with a side length of r are obtained as target pixel points, or pixel points within a rectangular area centered on this pixel point with a long side of m and a wide side of n are obtained as target pixel points. It can be understood that the above three methods are only specific examples in this embodiment and do not constitute limitations. The specific range for obtaining target pixel points can be flexibly set according to actual needs.

[0039] Step S302: Calculate the average brightness of at least some of the target pixel points as the ambient light brightness value at this pixel point.

[0040] Specifically, in this step, it can be to calculate the average brightness of all the target pixel points as the ambient light brightness value at this pixel point, or it can be to obtain some of the target pixel points from multiple target pixel points for average calculation, which can be flexibly set according to actual needs.

[0041] Next, an example of the method for obtaining some of the target pixel points from multiple target pixel points is given. The specific steps are as Figure 4 shown, including:

[0042] Step S401: Sort all the target pixel points in descending order of brightness.

[0043] Step S402: Calculate the average brightness of the target pixel points ranked in the top N as the ambient light brightness value, where N is a positive integer greater than 1.

[0044] Specifically, in this step, for example, the target pixel points ranked in the top 6, top 10, or top 20 are obtained for average brightness calculation, which can be flexibly set according to actual needs. For example, it can be obtained according to the number of target pixel points obtained, and the target pixel points ranked in the top 1 / 3 or 1 / 2 of the number of target pixel points are obtained for average brightness calculation.

[0045] Preferably, in other embodiments of the present invention, before calculating the average brightness of the target pixel points ranked in the top N, the target pixel point ranked first is excluded, and the remaining target pixel points are re-sorted in descending order of brightness. Excluding the target pixel point ranked first and re-sorting the target pixel points can reduce the influence of extreme cases on the calculation result, improve the accuracy of the ambient light brightness value calculation, and further improve the accuracy of defect detection.

[0046] Step S202: Perform brightness compensation on the brightness of the pixel point according to the ambient light brightness value.

[0047] Specifically, in this step, the steps of performing brightness compensation on the brightness of pixel points according to the ambient light brightness value are as follows Figure 5 shown, including the following steps:

[0048] Step S501: Obtain the brightness of the pixel point in the sampled image as the pixel brightness value.

[0049] Step S502: Determine whether the ambient light brightness value corresponding to the pixel point is greater than the pixel brightness value corresponding to it; if not, execute Step S503; if so, execute Step S504.

[0050] Step S503: Output the compensation brightness value as 255.

[0051] Step S504: Output the compensation brightness value as 255 - (A - B), where A is the background brightness value and B is the pixel brightness value.

[0052] Step S505: Replace the pixel brightness value of the pixel point with the compensation brightness value.

[0053] Step S104: Perform defect detection on the target image to obtain the defect positions in the target image.

[0054] Next, the defect detection process in this step will be illustrated by examples. It can be understood that the following are only two specific examples of the defect detection process in this embodiment, and do not constitute a limitation. In other embodiments of the present invention, other methods may also be used for defect detection, which can be flexibly applied according to actual needs.

[0055] Example 1: Perform binarization processing on the target image, for example, use the OTSU algorithm or the Sauvola algorithm to perform binarization processing on the target image. Calculate the average value of the brightness of each pixel point in the binarized target image; regard the pixel points with brightness less than the average value as the pixel points with display defects.

[0056] Among them, the Sauvola algorithm includes: First, according to the formula

[0057]

[0058] calculate the gray mean value m(x, y) and the standard variance s(x, y) within the r*r neighborhood of the pixel point;

[0059] Then, according to the formula

[0060] calculate the threshold T(x, y) of the pixel point.

[0061] Wherein, R is the dynamic range of the standard variance. If the current input image is an 8-bit grayscale image, then R = 128; k is a preset constant, where 0 < k < 1.

[0062] Example 2: After obtaining the target image, according to the distribution of different process blocks of the display screen to be measured, the target image is segmented into at least two blocks. In some embodiments, each process block is divided into one block. After the block segmentation of the target image is completed, the parameters of each block are obtained, such as the position, shape, and polarization degree of each block; a corresponding detection algorithm is matched for each block according to the parameters of each block, and then a preset type of defect detection is performed on each block according to the matched algorithm to obtain a defect detection result.

[0063] It can be understood that the types of defects corresponding to different block processes may be the same or different, and the detection algorithms corresponding to different defect types may be the same or different. Therefore, it is necessary to analyze the defects of each block through one or more detection algorithms.

[0064] Wherein, each detection algorithm includes settable preset detection parameters, and the preset detection parameters include but are not limited to accuracy parameters and contrast parameters.

[0065] After the detection algorithm for each block is matched, preset detection parameters are set for the detection algorithm of each block, and then the corresponding detection algorithm is used to perform defect detection on each block to obtain a defect detection result corresponding to the current preset detection parameters. Taking the accuracy parameter as an example, the same detection algorithm is used to analyze the same block, and the accuracy A is lower than the accuracy B. At the level of accuracy A, defect A can be detected, and at the level of accuracy B, defect A and defect B can be detected. Then, when the current accuracy level is A, the detection algorithm only outputs defect A, and when the current accuracy level is B, the detection algorithm outputs defect A and defect B. Wherein, the defects include but are not limited to at least one of spot (dot-like) defects, Line (linear) defects, Rubbin defects, band (band-like) defects, omniLine (omnidirectional linear) defects, Side (edge-like) defects, Twill (twill-like) defects (twill defects), grid (grid-like) defects.

[0066] Compared with the prior art, in the display screen display defect detection method provided by the first embodiment of the present invention, after obtaining a sampling image by photographing a display screen showing a sample image, before performing defect detection on the sampling image, brightness noise removal processing is also performed on each pixel point in the sampling image, and the brightness of the pixel point is compensated by calculating the ambient light brightness value at the pixel point, so as to remove the influence of ambient light on the brightness value of the pixel point, and a target image with the influence of ambient light on brightness removed is obtained. Performing defect detection on the target image can avoid the influence of ambient light on the defect detection result and improve the accuracy of the defect detection result.

[0067] The second embodiment of the present invention relates to a method for detecting display defects of a display screen. The second embodiment is substantially the same as the first embodiment, and also includes steps S101 to S104 as shown in Figure 1 The main difference is that: in the first embodiment, the step of performing brightness compensation on the brightness of pixel points according to the ambient light brightness value is as shown in Figure 5 In the second embodiment of the present invention, the step of performing brightness compensation on the brightness of pixel points according to the ambient light brightness value is as shown in Figure 6 shown, including:

[0068] Step S601: Obtain the brightness of the pixel point in the sampled image as the pixel brightness value.

[0069] Step S602: Determine whether the ambient light brightness value corresponding to the pixel point is greater than the pixel brightness value corresponding to it; if not, execute step S603; if so, execute step S604.

[0070] Step S603: Output the compensated brightness value as 255.

[0071] Step S604: Output the compensated brightness value as 255 - (A - B), where A is the background brightness value and B is the pixel brightness value.

[0072] Step S605: Determine the contrast expansion coefficient k according to the pixel brightness value, and change the compensated brightness value to 255 - k*(A - B).

[0073] Specifically, in this step, according to the formula

[0074] Determine the contrast expansion coefficient k;

[0075] where B1 and B2 are preset constants, such as B1 = 2.5, B2 = 1.0, etc., and I b (x, y) is the pixel brightness value of this pixel point.

[0076] Step S606: Replace the pixel brightness value of the pixel point with the compensated brightness value.

[0077] Compared with the prior art, while retaining the technical effects of the first embodiment, the second embodiment of the present invention determines the contrast expansion coefficient k according to the pixel brightness value, and adjusts the compensated brightness value according to the contrast expansion coefficient k, so as to increase the contrast between each pixel, improve the accuracy of the calculation result, and further improve the accuracy of the defect detection result.

[0078] Preferably, in another embodiment of the present invention, after step S605, it further includes: determining whether 255 - k*(A - B) is less than 191; if so, changing the compensation brightness value to 191 and then executing step S606; if not, directly executing step S606. By judging the value of 255 - k*(A - B) and the brightness value of 191, it is possible to avoid extremely low brightness values in the output brightness values, and reduce the influence of extreme situations on the defect detection results.

[0079] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, they are all within the protection scope of this patent; making insignificant modifications to the algorithm or process or introducing insignificant designs, but without changing the core design of its algorithm and process are all within the protection scope of this patent.

[0080] The third embodiment of the present invention relates to a display defect detection device for a display screen, as Figure 7 shown, including: at least one processor 701; and a memory 702 communicatively connected to the at least one processor 701; wherein, the memory 702 stores instructions executable by the at least one processor 701, and the instructions are executed by the at least one processor 701 so that the at least one processor 701 can execute the display defect detection method as described above.

[0081] Among them, the memory 702 and the processor 701 are connected by a bus. The bus can include any number of interconnected buses and bridges. The bus connects various circuits of one or more processors 701 and the memory 702 together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art. Therefore, they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor 701 is transmitted on the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor 701.

[0082] The processor 701 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. And the memory 702 can be used to store the data used by the processor 701 when performing operations.

[0083] The fourth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method embodiments described above are implemented.

[0084] That is, those skilled in the art can understand that all or part of the steps in the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0085] Those of ordinary skill in the art can understand that the above embodiments are specific examples for implementing the present invention, and in actual applications, various changes can be made to them in form and details without departing from the spirit and scope of the present invention.

Claims

1. A method for detecting display defects of a display screen, which is used to detect a display screen displaying a sample image, characterized in that, it includes: Obtain a sampled image, where the sampled image is an image obtained by photographing the display screen displaying the sample image; Obtain each pixel point in the sampled image; Perform brightness impurity removal processing on each pixel point respectively to obtain a target image; Perform defect detection on the target image to obtain the defect positions in the target image; Among them, the brightness impurity removal processing includes: Calculate the ambient light brightness value at the pixel point, where the ambient light brightness value is the brightness value of the ambient light outside the display screen at the pixel point, and perform brightness compensation on the brightness of the pixel point according to the ambient light brightness value; The performing brightness compensation on the brightness of the pixel point according to the ambient light brightness value specifically includes: Obtain the brightness of the pixel point in the sampled image as the pixel brightness value; Judge whether the ambient light brightness value corresponding to the pixel point is greater than its corresponding pixel brightness value; If not, output the compensation brightness value as 255; If so, output the compensation brightness value as 255 - (A - B), where A is the background brightness value and B is the pixel brightness value; Replace the pixel brightness value of the pixel point with the compensation brightness value.

2. The method for detecting display defects of a display screen according to claim 1, characterized in that, the calculating the ambient light brightness value at the pixel point specifically includes: Obtain other pixel points within a preset range around the pixel point to obtain a plurality of target pixel points; Calculate the brightness average value of at least part of the target pixel points as the ambient light brightness value at the pixel point.

3. The method for detecting display defects of a display screen according to claim 2, characterized in that, the calculating the brightness average value of at least part of the target pixel points specifically includes: Sort the target pixel points in descending order of brightness; Calculate the brightness average value of the target pixel points ranked in the first N positions as the ambient light brightness value, where N is a positive integer greater than 1.

4. The method for detecting display defects of a display screen according to claim 3, characterized in that, before calculating the brightness average value of the target pixel points ranked in the first N positions, it further includes: Exclude the target pixel point ranked first; Re - sort the remaining target pixel points in descending order of brightness.

5. The method for detecting display defects of a display screen according to claim 1, characterized in that, after outputting the compensation brightness value as 255 - (A - B) and before replacing the pixel brightness value of the pixel point with the compensation brightness value, it further includes: Determine the contrast expansion coefficient k according to the pixel brightness value, and change the compensation brightness value to 255 - k*(A - B).

6. The method for detecting display defects of a display screen according to claim 5, characterized in that, after changing the compensation brightness value to 255 - k*(A - B) and before replacing the pixel brightness value of the pixel point with the compensation brightness value, it further includes: Judge whether 255 - k*(A - B) is less than 191; If so, change the compensation brightness value to 191.

7. The display defect detection method for a display screen according to claim 1, wherein, the defect detection of the target image specifically includes: performing binarization processing on the target image, and performing defect detection on the binarized target image; calculating the average value of the brightness of each pixel point in the binarized target image; and taking the pixel points with brightness less than the average value as the pixel points with display defects.

8. A display defect detection device for a display screen, wherein, it includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the display defect detection method according to any one of claims 1 to 7.

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