Abnormality detection method and computer readable storage medium

Abstract

The invention discloses an anomaly detection method and a computer readable storage medium, and the method comprises the steps: obtaining first brightness compensation values corresponding to a plurality of first pixel units in a first image, and enabling a camera to shoot a first panel at a first gray scale to obtain the first image; dividing an area where the plurality of first pixel units are distributed in the first image into a plurality of first areas; according to the first brightness compensation values corresponding to the plurality of first pixel units, respectively generating a target parameter value corresponding to each first area; and determining whether the brightness compensation of the first panel is abnormal or not according to the target parameter values corresponding to the plurality of first areas. Through the method, the De-Mura newly-added abnormity can be recognized in advance, and the detection efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of display panel detection, and in particular to an abnormality detection method and a computer storage medium. Background Art

[0002] In the manufacturing of the display industry, Mura is the most common display defect, which generally refers to the phenomenon of uneven brightness of the display. In order to improve the display effect of the display, it is usually necessary to compensate the uneven brightness of the screen to the target brightness to achieve a uniform display effect.

[0003] However, the brightness compensation method in the prior art is prone to compensation abnormality. Summary of the invention

[0004] The main technical problem solved by the present application is to provide an anomaly detection method and a computer storage medium, which can identify new anomalies of De-Mura in advance and improve detection efficiency.

[0005] In order to solve the above technical problems, a technical solution adopted in the present application is: to provide an abnormality detection method, the method comprising: obtaining first brightness compensation values ​​corresponding to multiple first pixel units in a first image, wherein the first image is obtained by a camera shooting a first panel at a first grayscale; dividing the area where the multiple first pixel units are distributed in the first image into multiple first areas; according to the first brightness compensation values ​​corresponding to the multiple first pixel units, respectively generating target parameter values ​​corresponding to each first area; according to the target parameter values ​​corresponding to the multiple first areas, determining whether there is an abnormality in the brightness compensation of the first panel.

[0006] The method further includes: lighting up a plurality of sub-pixels of the first panel whose luminous color is the target color under the first gray scale; and controlling the camera to shoot the first panel to obtain the first image.

[0007] Wherein, the target color includes red, green or blue.

[0008] The step of generating a target parameter value corresponding to each first region according to the first brightness compensation values ​​corresponding to the plurality of first pixel units, comprises: for each first region, determining a second region in the second image having the same position as the first region, and determining the target parameter value corresponding to the first region according to the first brightness compensation value corresponding to the first pixel unit in the first region and the second brightness compensation value corresponding to the second pixel unit corresponding to the second region, wherein the position of the second pixel unit corresponding to the first pixel unit in the second region is the same as the position of the first sub-pixel in the first region, the second image is obtained by the camera photographing a second panel at the first grayscale, the second panel is a previously detected panel of the first panel, and the closer the first brightness compensation value of the first pixel unit in the first region is to the second brightness compensation value of the second pixel unit in the second region, the larger the target parameter value corresponding to the first region; and the step of determining whether the brightness compensation of the first panel is abnormal according to the plurality of target parameter values ​​corresponding to the first regions, comprises: determining that the brightness compensation of the first panel is abnormal in response to the target parameter value corresponding to any of the first regions being greater than the first parameter threshold.

[0009] Wherein, the first gray scale is greater than or equal to 32.

[0010] Among them, the step of calculating the first brightness compensation value of the first pixel unit in the first area and the second brightness compensation value of the corresponding second pixel unit in the second area at the first grayscale includes: calculating the absolute value of the brightness difference between the first brightness compensation value of the first pixel unit in the first area and the second brightness compensation value of the corresponding second pixel unit in the second area, and obtaining multiple absolute values ​​corresponding to the first area; determining the proportion of the absolute values ​​that are less than the difference threshold among the multiple absolute values ​​corresponding to the first area, and determining the proportion as the target parameter value corresponding to the first area.

[0011] The first parameter threshold ranges from 40% to 100%.

[0012] Among them, the step of generating a target parameter value corresponding to each first area according to the first brightness compensation values ​​corresponding to the multiple first pixel units, includes: for each first area, according to the first brightness compensation values ​​of the first pixel units in the first area, calculating the average value, median value or mode value of the absolute value of the first brightness compensation value, to obtain the target parameter value corresponding to the first area; and the step of determining whether the brightness compensation of the first panel is abnormal according to the target parameter values ​​corresponding to the multiple first areas, includes: in response to the difference between the target parameter values ​​corresponding to any two adjacent first areas exceeding the range of the second parameter threshold, determining that the brightness compensation of the first panel is abnormal.

[0013] Wherein, the first gray scale is greater than or equal to 32.

[0014] Among them, the step of determining that an abnormality occurs in the brightness compensation of the first panel in response to the difference between the target parameter values ​​corresponding to any two adjacent first areas being greater than a second parameter threshold includes: determining that an abnormality occurs in the brightness compensation of the first panel in response to the ratio of the target parameter values ​​corresponding to any two adjacent first areas being outside the range of the second parameter threshold.

[0015] The range of the second parameter threshold is 0.6-1.5.

[0016] Among them, the step of generating a target parameter value corresponding to each of the first regions according to the first brightness compensation values ​​corresponding to the multiple first pixel units, includes: determining a median value of the first brightness compensation value according to the first brightness compensation values ​​corresponding to the multiple first pixel units; for each of the first pixel units, calculating a ratio of the first brightness compensation value of the first pixel unit to the median value to obtain a ratio corresponding to the first pixel unit; for each of the first regions, determining the target parameter value corresponding to the first region according to the ratio corresponding to the first pixel unit in the first region, wherein the larger the ratio corresponding to the first pixel unit in the first region, the larger the target parameter value corresponding to the first region; and the step of determining whether an abnormality occurs in the brightness compensation of the first panel according to the target parameter values ​​corresponding to the multiple first regions, includes: determining that an abnormality occurs in the brightness compensation of the first panel in response to the target parameter value corresponding to any of the first regions being greater than a third parameter threshold.

[0017] The method further includes: after determining that brightness compensation of the first panel is abnormal, determining that light leakage occurs during the detection process.

[0018] Wherein, the first gray scale is less than or equal to 32.

[0019] Among them, the step of determining the target parameter value corresponding to the first area based on the ratio corresponding to the first pixel unit in the first area includes: determining the proportion of the ratios corresponding to the first area that exceeds a ratio threshold, and determining the proportion as the target parameter value corresponding to the first area.

[0020] The range of the third parameter threshold is 40%-100%.

[0021] The method further includes: taking a plurality of different test grayscales as the first grayscale in sequence, and then executing the step of obtaining the first brightness compensation values ​​of the plurality of first pixel units in the first panel at the first grayscale to the step of determining whether an abnormality occurs in the brightness compensation of the first panel according to the target parameter values ​​corresponding to the plurality of first regions; in response to determining that no abnormality occurs in the brightness compensation of the first display panel at the plurality of test grayscales, it is finally determined that no abnormality occurs in the brightness compensation of the first panel.

[0022] Wherein, the number of the test grayscales is greater than or equal to 3.

[0023] The grayscale values ​​of the test grayscale include 16, 128 and 224.

[0024] To solve the above technical problems, another technical solution adopted by the present application is: providing a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program can be executed by a processor to implement the steps in the method of any embodiment.

[0025] The beneficial effect of the present application is that, different from the prior art, the abnormality detection method of the present application collects brightness compensation data in the De-Mura process, divides the image into multiple first areas, and analyzes and compares the target parameter values ​​corresponding to the first areas. It can identify in advance whether there are external factors affecting the brightness compensation before the brightness compensation, causing abnormalities in the subsequent brightness compensation, thereby improving the detection efficiency and reducing the number of abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of an implementation method of an abnormality detection method of the present application;

[0027] Figure 2 is a schematic diagram of an implementation method of a first brightness value, a target brightness value and a first brightness compensation value in the present application;

[0028] Figure 3 It is a flowchart of an implementation method of an abnormality detection method of the present application;

[0029] Figure 4 yes Figure 3 A schematic flow chart of an implementation method of step S230;

[0030] Figure 5 is a schematic diagram of an implementation method of a first brightness compensation value, a second brightness compensation value, a difference value and a target parameter value in the present application;

[0031] Figure 6 It is a flowchart of an implementation method of an abnormality detection method of the present application;

[0032] Figure 7 is a schematic diagram of an implementation method of an absolute value, an average value and a ratio of the average values ​​in the present application;

[0033] Figure 8 It is a flowchart of another implementation method of the anomaly detection method of the present application;

[0034] Fig. 9 is a schematic diagram of an implementation method of a first brightness compensation value, a ratio and a target parameter value in the present application;

[0035] Fig.10 It is a schematic diagram of a framework of an electronic device of the present application;

[0036] Fig.11 It is a schematic diagram of a framework of an implementation scheme of a computer-readable storage medium of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and effect of the present application clearer and more specific, the present application is further described in detail with reference to the accompanying drawings and examples. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0038] In related technologies, an optical compensation method is generally used to achieve brightness compensation. The principle is: after the display panel is powered on, several groups of photos are taken with a camera. The brightness value that needs to be compensated for each point is calculated based on the difference between the actual brightness value of each point in the photo and the target brightness. The compensation data is then burned into the driver chip to achieve a uniform display effect. This is called the De-Mura process.

[0039] However, in actual practice, factors other than the screen itself, such as foreign matter in the camera, foreign matter on the screen surface, algorithm parameters, camera parameters, light leakage, or equipment matching, can cause the brightness value in the photo taken by the camera to be different from the actual brightness value of the screen, which will lead to differences in the brightness compensation value. When the wrong compensation value is superimposed on the display, a brightness that does not match the target value will appear at the corresponding position, resulting in a new De-Mura anomaly.

[0040] In view of the above problems, this application provides an anomaly detection method to identify new anomalies added by De-Mura. Figure 1 , Figure 1 1 is a flowchart of an implementation method of an anomaly detection method of the present application. The anomaly detection method comprises the following steps:

[0041] S110: Acquire first brightness compensation values ​​corresponding to a plurality of first pixel units in a first image, wherein the first image is obtained by photographing a first panel at a first grayscale with a camera.

[0042] Specifically, in this step, first, under the first grayscale, a plurality of sub-pixels of the target color in the first panel are lit. The first grayscale can be any value in 0-255 (e.g., 16, 128, 224, etc.), the target color can be red, green, or blue, the first panel is the display panel to be detected, and the plurality of sub-pixels can be all sub-pixels of the same luminous color in the first panel, or can be some sub-pixels of the same luminous color. After being lit, the luminous color and grayscale value of the entire surface of the first panel are the same, that is, light of uniform color and brightness is emitted. Then, the camera is controlled to shoot the illuminated first panel to obtain a first image.

[0043] The first image is an image captured by the camera, and each first brightness compensation value in the first image is a brightness compensation value corresponding to each pixel unit (i.e., the first pixel unit) of the camera. It should be noted that since the resolution of the camera and the display panel are not necessarily the same, the first pixel unit and the pixel unit of the first panel do not necessarily correspond one to one.

[0044] Specifically, the first brightness compensation value is obtained in the following manner: first, the first brightness values ​​corresponding to the plurality of first pixel units in the first image are obtained. The first brightness value of a certain pixel unit in the first image is the brightness value after the actual brightness value of the corresponding position of the first panel is superimposed with the external influencing factors. The external influencing factors may be camera foreign matter, screen surface foreign matter, algorithm parameters, camera parameters, light leakage or equipment matching, etc., wherein camera foreign matter and screen surface foreign matter may cause the first brightness value in the first image to be lower than the actual brightness value of the first panel, and light leakage may cause the first brightness value in the first image to be higher than the actual brightness value of the first panel. Then, for each first pixel unit, the target brightness value of the first panel at the first grayscale is subtracted from the first brightness value to obtain the first brightness compensation values ​​corresponding to the plurality of first pixel units in the first image.

[0045] For ease of understanding, here are some examples and references Figure 2 The method for obtaining the first brightness compensation value is described below:

[0046] First, all red sub-pixels in the first panel are lit at a first grayscale with a grayscale value of 224, so that the first panel emits red light, a camera is controlled to shoot the first panel to obtain a first image, and first brightness values ​​corresponding to a plurality of first pixel units in the first image are obtained. Figure 2 (a) shows first brightness values ​​corresponding to a plurality of first pixel units in the first image. Figure 2 (b) shows the target brightness value of the first panel. For each first pixel unit, the target brightness value 224 is subtracted from the first brightness value. Figure 2 (b) and Figure 2 Subtract the values ​​of (a) to get Figure 2 (c) in the figure shows the first brightness compensation values ​​corresponding to multiple first pixel units in the first image at the first grayscale.

[0047] S120: Divide the area where the plurality of first pixel units are distributed in the first image into a plurality of first areas.

[0048] In one embodiment, a plurality of first regions are arranged in a matrix, and the first region includes at least one first pixel unit, for example Figure 2 As shown in (c), the area where the plurality of first pixel units are distributed in the first image is divided into 16 first areas, each of which includes 5x5 first pixel units, and each of which corresponds to 25 first brightness compensation values. In other embodiments, the first area may be other numbers, and the first area may also include other numbers of first pixel units.

[0049] Of course, in other implementations, the plurality of first regions may also be arranged in a non-matrix manner.

[0050] S130: Generate a target parameter value corresponding to each first area according to the first brightness compensation values ​​corresponding to the plurality of first pixel units.

[0051] The target parameter value is used to characterize the brightness compensation degree or compensation change degree of each first area.

[0052] S140: Determine whether brightness compensation of the first panel is abnormal according to target parameter values ​​corresponding to the plurality of first regions.

[0053] Specifically, when the target parameter value corresponding to at least one first area meets the preset conditions, it is determined that an abnormality has occurred in the brightness compensation of the first panel, that is, a brightness influencing factor outside the screen body appears during the detection process. In some embodiments, the target parameter value corresponding to each first area can be calculated separately. As long as one or more of the first areas meet the conditions, it is determined that an abnormality has occurred in the brightness compensation of the first panel to be detected. In other embodiments, the target parameter value corresponding to the first first area can be calculated first. If the target parameter value does not meet the preset conditions, the target parameter value corresponding to the next first area is calculated continuously until a target parameter value corresponding to a first area meets the preset conditions, that is, the calculation is stopped and it is determined that an abnormality has occurred in the brightness compensation of the first panel. If the target parameter values ​​corresponding to all first areas do not meet the preset conditions, there is no abnormality in the brightness compensation of the first panel.

[0054] The method provided in the present application collects brightness compensation data during the De-Mura process, divides the image into multiple first areas, and analyzes and compares the target parameter values ​​corresponding to the first areas. It can identify in advance whether there are external factors affecting the brightness compensation before the brightness compensation, causing abnormalities in the subsequent brightness compensation, thereby improving the detection efficiency and reducing the number of abnormalities.

[0055] The types of external brightness influencing factors can be divided into foreign matter (including camera foreign matter and screen foreign matter), abnormal camera parameters and light leakage, among which foreign matter and camera parameters usually cause the brightness value of some areas to decrease, so they are easier to measure in the state of high grayscale (grayscale value of 32-255); while light leakage usually causes the brightness value of some areas to increase, so it is easier to measure in the state of low grayscale (grayscale value of 0-16). The target parameter value can be generated in different ways according to the type of brightness influencing factor.

[0056] See also Figure 3 , Figure 3 This is a flow chart of another embodiment of the abnormality detection method of the present application. The detection method can be used to determine the problem of camera foreign matter or camera parameter difference, which leads to abnormal brightness compensation. The method includes the following steps:

[0057] S210: Obtaining first brightness compensation values ​​corresponding to a plurality of first pixel units in a first image, wherein the first image is obtained by photographing a first panel at a first grayscale by a camera.

[0058] Step S210 is the same as step S110, and the first gray scale is greater than or equal to 32, that is, the test is performed at a high gray scale.

[0059] S220: Divide the area where the plurality of first pixel units are distributed in the first image into a plurality of first areas.

[0060] Step S220 is the same as step S120 and will not be described again here.

[0061] S230: For each first region, determine a second region in the second image that is located at the same position as the first region, and determine a target parameter value corresponding to the first region based on a first brightness compensation value corresponding to a first pixel unit in the first region and a second brightness compensation value corresponding to a corresponding second pixel unit in the second region.

[0062] Among them, the position of the second pixel unit corresponding to the first pixel unit in the second area is the same as the position of the first sub-pixel in the first area, the second image is obtained by the camera shooting the second panel at the first grayscale, the second panel is the previous detected panel of the first panel, and the closer the first brightness compensation value of the first pixel unit in the first area is to the second brightness compensation value of the second pixel unit in the second area, the larger the target parameter value corresponding to the first area is.

[0063] In the actual detection process, the same device is usually used to detect multiple display panels in sequence. If an abnormality such as foreign matter appears on the device, the brightness compensation of the same position of each display panel will be abnormal after the foreign matter appears. This step is used to compare the brightness compensation value of the area at the same position in the first panel to be detected and the second panel that has been detected before. The acquisition method and acquisition conditions of the second brightness compensation value are the same as those of the first brightness compensation value, that is, the first image and the second image are acquired at the same grayscale, and the luminous color of the display panel is the same, the number of first pixel units included in the first area and the number of second pixel units included in the second area, and the position of the first area in the first image and the position of the second area in the second image are the same. The target parameter value is used to characterize the degree of change of the first brightness compensation value of the first area compared to the second brightness compensation value of the same position (i.e., the second area) of the previous panel. The smaller the degree of change, the larger the target parameter value. At the same time, since the first brightness compensation value and the second brightness compensation value are obtained at the same grayscale, the smaller the degree of change of the brightness compensation value, the smaller the degree of change of the brightness value of the area.

[0064] S240: In response to the target parameter value corresponding to any first area being greater than the first parameter threshold, determining that brightness compensation for the first panel is abnormal.

[0065] Specifically, when the target parameter value is greater than the first parameter threshold, it means that under the same detection conditions, the brightness values ​​of the same area of ​​two consecutive display panels change only to a small extent, indicating that there is foreign matter blocking the light in the fixed area or the camera parameters are abnormal. An alarm can be issued to prompt engineers to investigate the cause.

[0066] Specifically, see Figure 4 , Figure 4 yes Figure 3 The flowchart of step S230 in the embodiment includes the following steps:

[0067] S231: Calculate the absolute value of the brightness difference between a first brightness compensation value of a first pixel unit in the first area and a second brightness compensation value of a corresponding second pixel unit in the second area to obtain a plurality of absolute values ​​corresponding to the first area.

[0068] Specifically, the absolute value of the difference in brightness compensation value is calculated for each first pixel unit in the first region. For example, when there are 25 first pixel units in the first region, the absolute value of the difference between the first brightness compensation value of each first pixel unit and the second brightness compensation value of the second pixel unit at the same position of the previous display panel is calculated respectively, that is, there are 25 absolute values ​​in the first region.

[0069] S232: Determine the proportion of the absolute values ​​that are less than the difference threshold among the multiple absolute values ​​corresponding to the first area, and determine the proportion as the target parameter value corresponding to the first area.

[0070] In one embodiment, when there are 25 first pixel units in the first region, the target parameter value is the ratio of the number of 25 absolute values ​​less than the difference threshold to 25. Specifically, the difference threshold may be a fixed value, such as 3, 4, 5, ..., or adjusted according to the first grayscale, and the difference threshold may be positively correlated with the first grayscale, such as when the first grayscale is 224, the difference threshold is 5, when the first grayscale is 128, the difference threshold is 4, when the first grayscale is 32, the difference threshold is 3, etc. Specifically, the range of the first parameter threshold is 40%-100%.

[0071] For ease of understanding, here are some examples and references Figure 5 The following describes how to obtain the target parameter value:

[0072] Taking the first grayscale as 224, the difference threshold as 5, and the first parameter threshold as 50% as an example, first obtain Figure 5 The first brightness compensation value corresponding to the first image shown in (a) is retrieved and the ... Figure 5 The second brightness compensation value corresponding to the second image of the second panel shown in (b) is calculated for each pixel unit. The difference between the first brightness compensation value and the second brightness compensation value is obtained by subtracting the values ​​of (b) from (a). Figure 5 (c) in FIG. 1 shows the difference between the first brightness compensation value and the second brightness compensation value, and the difference with an absolute value less than 5 is marked in the figure. The target parameter value is calculated for each first area, that is, the number of differences with an absolute value less than 5 in each first area in FIG. (c) is calculated and divided by 25 (the total number of differences in each first area), and the target parameter value is obtained. Figure 5 (d) shows the ratio of the number of differences with an absolute value less than 5 in each first region to 25. As can be seen from the figure, there are two first regions (shown in the dotted box) with a ratio greater than 50% (64% and 60% respectively), and the target parameter values ​​corresponding to two first regions in the first image are greater than the difference threshold. It can be determined that the positions corresponding to at least two regions of the first panel have camera foreign matter or parameter abnormalities, resulting in abnormalities in subsequent brightness compensation.

[0073] In other embodiments, the target parameter value corresponding to the first area can be calculated in units of the first area, and it is determined whether the target parameter value is greater than the difference threshold. If the target parameter value is less than or equal to the difference threshold, the target parameter value corresponding to the next first area is calculated. If the target parameter value is greater than the difference threshold, the calculation is stopped to determine that the brightness compensation of the first panel is abnormal. This method has higher detection efficiency.

[0074] See also Figure 6 , Figure 6 This is a flow chart of another embodiment of the abnormality detection method of the present application. The detection method can be used to determine the problem of screen foreign matter, camera foreign matter or camera parameter difference, which leads to abnormal brightness compensation. The method includes the following steps:

[0075] S310: Obtaining first brightness compensation values ​​corresponding to a plurality of first pixel units in a first image, wherein the first image is obtained by photographing a first panel at a first grayscale by a camera.

[0076] Step S310 is the same as step S110, and the first gray scale is greater than or equal to 32, that is, the test is performed at a high gray scale.

[0077] S320: Divide the area where the plurality of first pixel units are distributed in the first image into a plurality of first areas.

[0078] Step S320 is the same as step S120 and will not be described again here.

[0079] S330: For each first region, according to the first brightness compensation value of the first pixel unit in the first region, calculate the average value, median value or mode value of the absolute value of the first brightness compensation value to obtain the target parameter value corresponding to the first region.

[0080] The target parameter value is used to characterize the degree of brightness compensation of the first area.

[0081] S340: In response to the difference between the target parameter values ​​corresponding to any two adjacent first areas exceeding the range of the second parameter threshold, it is determined that the brightness compensation of the first panel is abnormal. Specifically, in response to the ratio of the target parameter values ​​corresponding to any two adjacent first areas being outside the range of the second parameter threshold, it is determined that the brightness compensation of the first panel is abnormal. The range of the second parameter threshold is 0.6-1.5. In other embodiments, it is also possible to determine whether an abnormality occurs by calculating the difference between the target parameter values ​​of any two adjacent first areas, and then comparing the difference with the second parameter threshold. Since the luminous brightness of the screen itself usually changes gradually, the change amplitude between adjacent areas is small, and foreign matter on the screen, foreign matter on the camera or abnormal parameters usually causes a large change amplitude in the edge brightness of the abnormal area. When the ratio of the target parameter values ​​corresponding to any two adjacent first areas is outside the range of the second parameter threshold, it indicates that the brightness compensation between the above-mentioned first area and the adjacent first area has a sudden change, so that it can be determined that the position corresponding to the first area of ​​the first panel has the above-mentioned external influencing factors, resulting in an abnormality in the subsequent brightness compensation, and an alarm can be issued to prompt engineers to investigate the cause.

[0082] For ease of understanding, here are some examples and references Figure 7 The following describes how to obtain the target parameter value:

[0083] Continuing with the example of the first grayscale being 224, first obtain Figure 7 The absolute value of the first brightness compensation value corresponding to the first image shown in (a) is calculated for each first region, and the average value of 25 absolute values ​​is obtained. Figure 7 For each first region in (b), the average value corresponding to the current first region is divided by the average value corresponding to the first region adjacent to its right, and the result is Figure 7 As can be seen from the figure, the ratios of the four first areas (shown in the dotted boxes) are beyond the range of 0.6-1.5, that is, the above four ratios are too small or too large, indicating that the brightness of at least four first areas has changed suddenly. It can be determined that the first panel has screen foreign matter, camera foreign matter or parameter abnormality.

[0084] In other embodiments, the target parameter values ​​corresponding to two adjacent first areas can also be calculated in units of the first area, and it is determined whether the ratio of the two adjacent target parameter values ​​exceeds the range of the second parameter threshold. If the ratio is within the range, the ratio corresponding to the next group of first areas is calculated. If the ratio exceeds the range of the second parameter threshold, the calculation is stopped to determine that the brightness compensation of the first panel is abnormal. This method has higher detection efficiency. In addition, the two adjacent first areas can be arranged left and right, or up and down, and the numerator and denominator of the ratio can also be interchanged, and this application does not make specific restrictions.

[0085] See also Figure 8 , Figure 8 This is a flow chart of another embodiment of the abnormality detection method of the present application. The detection method can be used to determine the light leakage problem that causes the brightness compensation to be abnormal. The method includes the following steps:

[0086] S410: Similar to step S110, since light leakage may cause excessive local brightness, the first grayscale is less than or equal to 16, that is, the test is performed at a low grayscale.

[0087] S420: The same as step S120, which will not be described again here.

[0088] S431: Determine a median value of the first brightness compensation value according to the first brightness compensation values ​​corresponding to the plurality of first pixel units.

[0089] Specifically, since the test is performed at a low grayscale, the change range of the brightness compensation value is small except for the light leakage area, and the light leakage area usually accounts for a small proportion of the entire area, so the median value of the first brightness compensation value usually corresponds to the brightness compensation value of the low grayscale and is not easily affected by the brightness of the light leakage area. The median value is used to characterize the degree of brightness compensation in the first image except for the light leakage area.

[0090] S432: For each first pixel unit, calculate a ratio of the first brightness compensation value of the first pixel unit to the median value to obtain a ratio corresponding to the first pixel unit.

[0091] Specifically, each first pixel unit corresponds to a ratio, and the ratio is used to characterize the degree to which the brightness compensation value of each first pixel unit deviates from the median value. The larger the ratio, the greater the degree of deviation.

[0092] S433: For each first region, determine a target parameter value corresponding to the first region according to a ratio corresponding to the first pixel unit in the first region, wherein a larger ratio corresponding to the first pixel unit in the first region is, a larger target parameter value corresponding to the first region is.

[0093] Specifically, the proportion of the ratios that exceed the ratio threshold in the ratios corresponding to the first area is determined, and the proportion is determined as the target parameter value corresponding to the first area. The target parameter value is used to characterize the degree of deviation of the brightness compensation of the first area. The larger the target parameter value, the greater the degree of deviation of the brightness compensation value of the first area. When there are 20 first pixel units in the first area, the target parameter value is the ratio of the number of the 20 ratios that are greater than the ratio threshold to 20. Specifically, the ratio threshold may be a fixed value, for example, 8, 10, 12... In other embodiments, the number of the ratios that exceed the ratio threshold in the ratios corresponding to the first area may also be determined, and the number may be determined as the target parameter value corresponding to the first area.

[0094] S440: In response to the target parameter value corresponding to any first area being greater than the third parameter threshold, determining that brightness compensation for the first panel is abnormal.

[0095] Specifically, the third parameter threshold ranges from 40% to 100%.

[0096] Optionally, the method further includes step S450: after determining that the brightness compensation of the first panel is abnormal, determining that the camera has a light leakage phenomenon.

[0097] For ease of understanding, here are some examples and references Fig. 9 The following describes how to obtain the target parameter value:

[0098] Taking the first grayscale as 16, the ratio threshold as 10, and the third parameter threshold as 50% as an example, first obtain Fig. 9 The first brightness compensation value corresponding to the first pixel unit in the first image shown in (a) is calculated, and the median value of all the first brightness compensation values ​​is 0.531095. Then each first brightness compensation value is divided by the median value to obtain Fig. 9 Next, for each first region (with 20 ratios), the ratio of the number of ratios greater than 10 to 20 is determined (ratios greater than 10 are marked), and this ratio is used as the target parameter value, and the obtained Fig. 9 The target parameter value shown in (c) in FIG. 1 is shown in FIG. 1 . As can be seen from the figure, there is a first area (shown in the dotted box) with a ratio of 60%, which is greater than 50%, that is, the above ratio is too large, indicating that the brightness of at least one first area suddenly increases, and it can be determined that light leakage occurs during the detection process.

[0099] In other embodiments, the target parameter value corresponding to the current first area can also be calculated in units of the first area, and it is determined whether the target parameter value is greater than the third parameter threshold. If the target parameter value is less than the third parameter threshold, the target parameter value corresponding to the next first area is calculated. If it exceeds the third parameter threshold, the calculation is stopped to determine that a light leakage anomaly occurs during the detection of the first panel. This method has higher detection efficiency.

[0100] Optionally, the method of the present application further includes: taking a plurality of different test grayscales as the first grayscale in sequence, and then executing step S110. Specifically, the number of test grayscales is greater than or equal to 3, including 16, 128 and 224. Of course, in other embodiments, the number of test grayscales may be greater, such as 10. In response to determining that there is no abnormality in the brightness compensation of the first display panel under a plurality of test grayscales, it is finally determined that there is no abnormality in the brightness compensation of the first panel. Optionally, sub-pixels with luminous colors of red, green and blue are lighted up respectively under each test grayscale, and tests are performed respectively. In response to determining that there is no abnormality in the brightness compensation of the first display panel under each test, it is finally determined that there is no abnormality in the brightness compensation of the first panel.

[0101] See also Fig.10 , Fig.10 1 is a schematic diagram of a display device of an embodiment of the present application. In this embodiment, the display device 100 includes a memory 111, a processor 112, and a communication circuit 113. The processor 112 is coupled to the memory 111 and the communication circuit 113 respectively. The memory 111 stores program data. The processor 112 executes the program data in the memory to implement the abnormality detection method of the present application.

[0102] The processor 112 may also be referred to as a CPU (Central Processing Unit). The processor 112 may be an integrated circuit chip having signal processing capabilities. The processor 112 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. A general-purpose processor may be a microprocessor or the processor 112 may also be any conventional processor 112, etc.

[0103] See also Fig.11 , Fig.11It is a schematic diagram of a framework of an implementation method of a computer-readable storage medium of the present application. The computer-readable storage medium 120 of the embodiment of the present application stores a program instruction 121, and the program instruction 121 implements the anomaly detection method provided by the present application when it is executed. Among them, the program instruction 121 can form a program file and be stored in the above-mentioned computer-readable storage medium 120 in the form of a software product, so that a computer device (which can be a personal computer, a server, or a network device, etc.) executes all or part of the steps of each implementation method of the present application. The aforementioned computer-readable storage medium 120 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, and a tablet.

[0104] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0105] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed methods, devices and systems can be implemented in other ways. For example, the device implementation described above is only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0108] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0109] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0110] The above are only implementation methods of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An anomaly detection method, characterized in that: The method comprises: Acquire first brightness compensation values ​​corresponding to a plurality of first pixel units in a first image, wherein the first image is obtained by photographing a first panel at a first grayscale by a camera; Dividing the region where the plurality of first pixel units are distributed in the first image into a plurality of first regions; Generating a target parameter value corresponding to each of the first regions according to the first brightness compensation values ​​corresponding to the plurality of first pixel units; It is determined whether an abnormality occurs in brightness compensation of the first panel according to the target parameter values ​​corresponding to the plurality of first regions.

2. The anomaly detection method according to claim 1, characterized in that: The method further comprises: At the first gray scale, lighting up a plurality of sub-pixels of the first panel whose light emission color is the target color; Controlling the camera to photograph the first panel to obtain the first image; Preferably, the target color includes red, green or blue.

3. The anomaly detection method according to claim 1, characterized in that: The step of generating a target parameter value corresponding to each of the first regions according to the first brightness compensation values ​​corresponding to the plurality of first pixel units comprises: For each of the first regions, a second region in the second image having the same position as the first region is determined, and the target parameter value corresponding to the first region is determined according to the first brightness compensation value corresponding to the first pixel unit in the first region and the second brightness compensation value corresponding to the second pixel unit corresponding to the second region, wherein the position of the second pixel unit corresponding to the first pixel unit in the second region is the same as the position of the first sub-pixel in the first region, the second image is obtained by photographing a second panel at the first grayscale by the camera, the second panel is a previously detected panel of the first panel, and the closer the first brightness compensation value of the first pixel unit in the first region is to the second brightness compensation value of the second pixel unit in the second region, the greater the target parameter value corresponding to the first region is; Furthermore, the step of determining whether the brightness compensation of the first panel is abnormal according to the target parameter values ​​corresponding to the plurality of first regions comprises: In response to the target parameter value corresponding to any of the first regions being greater than a first parameter threshold, determining that brightness compensation for the first panel is abnormal; Preferably, the first gray scale is greater than or equal to 32.

4. The anomaly detection method according to claim 3, characterized in that: The step of determining the first brightness compensation value of the first pixel unit in the first area and the second brightness compensation value of the corresponding second pixel unit in the second area at the first grayscale comprises: Calculating an absolute value of a brightness difference between the first brightness compensation value of the first pixel unit in the first area and the second brightness compensation value of the corresponding second pixel unit in the second area to obtain a plurality of absolute values ​​corresponding to the first area; Determine a ratio of the absolute values ​​corresponding to the first area that are less than a difference threshold, and determine the ratio as the target parameter value corresponding to the first area; Preferably, the first parameter threshold ranges from 40% to 100%.

5. The anomaly detection method according to claim 1, characterized in that: The step of generating a target parameter value corresponding to each of the first regions according to the first brightness compensation values ​​corresponding to the plurality of first pixel units comprises: For each of the first regions, according to the first brightness compensation values ​​of the first pixel units in the first region, calculating an average value, a median value or an absolute value of a mode value of the first brightness compensation values, to obtain the target parameter value corresponding to the first region; Furthermore, the step of determining whether the brightness compensation of the first panel is abnormal according to the target parameter values ​​corresponding to the plurality of first regions comprises: In response to a difference between the target parameter values ​​corresponding to any two adjacent first regions exceeding a range of a second parameter threshold, determining that brightness compensation of the first panel is abnormal; Preferably, the first gray scale is greater than or equal to 32.

6. The anomaly detection method according to claim 1, characterized in that: The step of determining that the brightness compensation of the first panel is abnormal in response to the difference between the target parameter values ​​corresponding to any two adjacent first regions being greater than a second parameter threshold comprises: In response to a ratio of the target parameter values ​​corresponding to any two adjacent first regions being outside a range of the second parameter threshold, determining that brightness compensation for the first panel is abnormal; Preferably, the second parameter threshold is in the range of 0.6-1.

5.

7. The anomaly detection method according to claim 1, characterized in that: The step of generating a target parameter value corresponding to each of the first regions according to the first brightness compensation values ​​corresponding to the plurality of first pixel units comprises: Determining a median value of the first brightness compensation value according to first brightness compensation values ​​corresponding to a plurality of the first pixel units; For each of the first pixel units, calculating a ratio of the first brightness compensation value of the first pixel unit to the median value, to obtain a ratio corresponding to the first pixel unit; For each of the first regions, determining the target parameter value corresponding to the first region according to the ratio corresponding to the first pixel unit in the first region, wherein a larger ratio corresponding to the first pixel unit in the first region is, a larger target parameter value corresponding to the first region is; Furthermore, the step of determining whether the brightness compensation of the first panel is abnormal according to the target parameter values ​​corresponding to the plurality of first regions comprises: In response to the target parameter value corresponding to any of the first regions being greater than a third parameter threshold, determining that brightness compensation for the first panel is abnormal; Preferably, the method further comprises: After determining that brightness compensation of the first panel is abnormal, determining that light leakage occurs during the detection process; Preferably, the first gray scale is less than or equal to 32.

8. The abnormality detection method according to claim 7, characterized in that: The step of determining the target parameter value corresponding to the first area according to the ratio corresponding to the first pixel unit in the first area comprises: Determine a proportion of the ratios corresponding to the first area that exceeds a ratio threshold, and determine the proportion as the target parameter value corresponding to the first area; Preferably, the third parameter threshold ranges from 40% to 100%.

9. The abnormality detection method according to claim 1, characterized in that: The method further comprises: Using a plurality of different test grayscales as the first grayscale in sequence, and then performing the steps of obtaining the first brightness compensation values ​​of the plurality of first pixel units in the first panel at the first grayscale to determining whether the brightness compensation of the first panel is abnormal according to the target parameter values ​​corresponding to the plurality of first regions; In response to determining that no abnormality occurs in the brightness compensation of the first display panel under the plurality of test grayscales, finally determining that no abnormality occurs in the brightness compensation of the first panel; Preferably, the number of the test grayscales is greater than or equal to 3; Preferably, the grayscale values ​​of the test grayscale include 16, 128 and 224.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program can be executed by a processor to implement the steps in the method according to any one of claims 1 to 9.

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