Anomaly detection method and computer-readable storage medium

Abstract

The application discloses an abnormality detection method and a computer readable storage medium. The abnormality detection method comprises the following steps: acquiring 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 gray scale by using a camera; dividing a region in which the plurality of first pixel units are distributed in the first image into a plurality of first regions; respectively generating target parameter values corresponding to each first region according to the first brightness compensation values corresponding to the plurality of first pixel units; and determining whether abnormality occurs in brightness compensation of the first panel according to the target parameter values corresponding to the plurality of first regions. The above method can identify De-Mura new abnormality in advance, and improve detection efficiency.

Description

Technical Field

[0001] This application relates to the field of display panel testing, and in particular to an anomaly detection method and a computer storage medium. Background Technology

[0002] In the display manufacturing industry, mura is the most common display defect, generally referring to uneven brightness on the monitor. To improve the display effect, it is usually necessary to compensate for the uneven brightness of the screen to the target brightness to achieve a uniform display effect.

[0003] However, existing brightness compensation methods are prone to compensation anomalies. Summary of the Invention

[0004] The main technical problem addressed by this application is to provide an anomaly detection method and computer storage medium that can identify new De-Mura anomalies in advance and improve detection efficiency.

[0005] To address the aforementioned technical problems, this application provides an anomaly detection method, comprising: acquiring first brightness compensation values ​​corresponding to a plurality of first pixel units in a first image, wherein the first image is obtained by a camera capturing a first panel at a first grayscale level; dividing the area where the plurality of first pixel units are distributed in the first image into a plurality of first regions; generating target parameter values ​​corresponding to each of the first regions based on the first brightness compensation values ​​corresponding to the plurality of first pixel units; and determining whether an anomaly has occurred in the brightness compensation of the first panel based on the target parameter values ​​corresponding to the plurality of first regions.

[0006] The method further includes: under the first grayscale, illuminating multiple sub-pixels in the first panel whose luminous color is the target color; controlling the camera to take a picture of the first panel to obtain the first image.

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

[0008] The step of generating a target parameter value for each first region based on the first brightness compensation value corresponding to the plurality of first pixel units includes: for each first region, determining a second region in the second image that is at the same position as the first region, and determining the target parameter value corresponding to the first region based on the first brightness compensation value corresponding to the first pixel unit in the first region and the second brightness compensation value corresponding to the corresponding second pixel unit in 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 capturing a 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 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 is; and the step of determining whether the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to the plurality of first regions includes: determining that the brightness compensation of the first panel is abnormal in response to any target parameter value corresponding to the first region being greater than a first parameter threshold.

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

[0010] The step of calculating the brightness compensation value of the first pixel unit in the first region and the second brightness compensation value of the corresponding second pixel unit in the second region 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 region and the second brightness compensation value of the corresponding second pixel unit in the second region to obtain a plurality of absolute values ​​corresponding to the first region; determining the proportion of the plurality of absolute values ​​corresponding to the first region that are less than the difference threshold, and determining the proportion as the target parameter value corresponding to the first region.

[0011] The threshold value of the first parameter is in the range of 40%-100%.

[0012] The step of generating target parameter values ​​for each first region based on the first brightness compensation values ​​corresponding to the plurality of first pixel units includes: for each first region, calculating the average, median, or mode of the absolute values ​​of the first brightness compensation values ​​based on the first brightness compensation values ​​of the first pixel units in the first region to obtain the target parameter value corresponding to the first region; and the step of determining whether the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to the plurality of first regions includes: 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 exceeding the range of a second parameter threshold.

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

[0014] 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 the second parameter threshold includes: determining that the brightness compensation of the first panel is abnormal in response to the ratio of the target parameter values ​​corresponding to any two adjacent first regions being outside the range of the second parameter threshold.

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

[0016] The step of generating a target parameter value for each first region based on the first brightness compensation values ​​corresponding to the plurality of first pixel units includes: determining the median value of the first brightness compensation values ​​based on the first brightness compensation values ​​corresponding to the plurality of first pixel units; calculating the ratio of the first brightness compensation value to the median value for each first pixel unit to obtain the ratio corresponding to the first pixel unit; determining the target parameter value corresponding to each first region based on the ratio corresponding to the first pixel units in the first region, wherein the larger the ratio corresponding to the first pixel units in the first 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 based on the target parameter values ​​corresponding to the plurality of first regions includes: determining that the brightness compensation of the first panel is abnormal in response to any target parameter value corresponding to the first region being greater than a third parameter threshold.

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

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

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

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

[0021] The method further includes: taking multiple different test gray levels as the first gray level in sequence, and then performing the step of obtaining the first brightness compensation value of multiple first pixel units in the first panel under the first gray level to the step of determining whether the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to the multiple first regions; in response to determining that the brightness compensation of the first display panel is not abnormal under multiple test gray levels, it is finally determined that the brightness compensation of the first panel is not abnormal.

[0022] The number of test gray levels 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-mentioned technical problems, another technical solution adopted in this application is to provide a computer-readable storage medium storing a computer program that can be executed by a processor to implement the steps in the method of any embodiment.

[0025] The beneficial effects of this application are as follows: Unlike the prior art, the anomaly detection method of this application collects brightness compensation data in the De-Mura process, divides the image into multiple first regions, and analyzes and compares the target parameter values ​​corresponding to the first regions. This allows for the early identification of whether external factors affect brightness compensation in advance, which may cause anomalies in subsequent brightness compensation, thereby improving detection efficiency and reducing the number of anomalies. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating one implementation of the anomaly detection method of this application;

[0027] Figure 2 This is a schematic diagram of an embodiment of the first brightness value, target brightness value, and first brightness compensation value in this application;

[0028] Figure 3 This is a flowchart illustrating one implementation of the anomaly detection method of this application;

[0029] Figure 4 yes Figure 3 A flowchart illustrating an implementation method for step S230;

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

[0031] Figure 6 This is a flowchart illustrating one implementation of the anomaly detection method of this application;

[0032] Figure 7 This is a schematic diagram illustrating an embodiment of the ratio of absolute value, average value, and average value in this application;

[0033] Figure 8 This is a flowchart illustrating another embodiment of the anomaly detection method of this application;

[0034] Figure 9 This is a schematic diagram of an embodiment of the first brightness compensation value, ratio, and target parameter value in this application;

[0035] Figure 10 This is a schematic diagram of the framework of one embodiment of the electronic device of this application;

[0036] Figure 11 This is a schematic diagram of a framework of one embodiment of the computer-readable storage medium of this application. Detailed Implementation

[0037] To make the objectives, technical solutions, and effects of this application clearer and more explicit, the following detailed description is provided with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0038] In related technologies, optical compensation is generally used to achieve brightness compensation. The principle is as follows: after the display panel is powered on and lit, several sets of photos are taken by 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 value. The compensation data is then burned into the driver chip to achieve a uniform display effect, which is called the De-Mura process.

[0039] However, in practice, factors other than the screen itself, such as foreign objects in the camera, foreign objects on the screen surface, algorithm parameters, camera parameters, light leakage, or device compatibility, can cause the brightness value in the photo taken by the camera to be different from the actual brightness value of the screen. This will lead to a difference in the brightness compensation value. When the incorrect compensation value is superimposed on the display screen, the brightness at the corresponding position will not match the target value, 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 in De-Mura. See also... Figure 1 , Figure 1 This is a flowchart illustrating one embodiment of the anomaly detection method of this application. The anomaly detection method includes the following steps:

[0041] S110: Obtain the first brightness compensation value corresponding to multiple first pixel units in the first image, wherein the first image is obtained by the camera taking a picture of the first panel in the first gray level.

[0042] Specifically, in this step, firstly, at the first grayscale level, multiple sub-pixels in the first panel whose emission color is the target color are illuminated. The first grayscale level can be any value between 0 and 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 multiple sub-pixels can be all sub-pixels in the first panel with the same emission color, or only some sub-pixels with the same emission color. After illumination, the entire first panel emits the same emission color and grayscale value, i.e., it emits light of uniform color and brightness. Then, the camera is controlled to capture an image of the illuminated first panel, obtaining the first image.

[0043] The first image is an image captured by the camera. Each first brightness compensation value in the first image corresponds to the brightness compensation value for each pixel unit (i.e., the first pixel unit) of the camera. It should be noted that since the resolutions of the camera and the display panel may not be the same, the first pixel unit may not correspond one-to-one with the pixel units of the first panel.

[0044] Specifically, the first brightness compensation value is obtained as follows: First, the first brightness values ​​corresponding to multiple 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 of the corresponding position of the first panel superimposed with the brightness value of external influencing factors. External influencing factors can be foreign objects in the camera, foreign objects on the screen surface, algorithm parameters, camera parameters, light leakage, or device compatibility, etc. Among them, foreign objects in the camera and foreign objects on the screen surface will cause the first brightness value in the first image to be lower than the actual brightness value of the first panel, while light leakage will 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 value corresponding to multiple first pixel units in the first image.

[0045] To facilitate understanding, examples and references are provided below. Figure 2 The method for obtaining the first brightness compensation value will be explained below:

[0046] First, at the first grayscale level of 224, all red sub-pixels in the first panel are illuminated, causing the first panel to emit red light. The camera is then used to capture an image of the first panel, and the first brightness values ​​corresponding to multiple first pixel units in the first image are obtained. Figure 2 (a) shows the 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, i.e. Figure 2 (b) and Figure 2 Subtracting the value of (a) from the value of (a) yields Figure 2 (c) in the figure shows the first brightness compensation value corresponding to a plurality of first pixel units in the first image at the first gray level.

[0047] S120: Divide the area where multiple first pixel units are distributed in the first image into multiple first regions.

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

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

[0050] S130: Generate target parameter values ​​for each first region based on the first brightness compensation values ​​corresponding to multiple first pixel units.

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

[0052] S140: Determine whether there is an abnormality in the brightness compensation of the first panel based on the target parameter values ​​corresponding to multiple first regions.

[0053] Specifically, if the target parameter value corresponding to at least one first region meets the preset condition, it is determined that the brightness compensation of the first panel is abnormal, that is, a brightness influencing factor outside the screen has appeared during the detection process. In some embodiments, the target parameter value corresponding to each first region can be calculated separately. As long as one or more of the first regions meet the condition, it is determined that the brightness compensation of the current first panel to be detected is abnormal. In other embodiments, the target parameter value corresponding to the first first region can be calculated first. If the target parameter value does not meet the preset condition, the target parameter value corresponding to the next first region can be calculated until the target parameter value corresponding to one first region meets the preset condition. At this point, the calculation stops and it is determined that the brightness compensation of the first panel is abnormal. If the target parameter values ​​corresponding to all first regions do not meet the preset condition, the brightness compensation of the first panel is not abnormal.

[0054] The method provided in this application acquires brightness compensation data during the De-Mura process, divides the image into multiple first regions, and analyzes and compares the target parameter values ​​corresponding to the first regions. This allows for early identification of external factors that may cause abnormalities in subsequent brightness compensation before brightness compensation, thereby improving detection efficiency and reducing the number of anomalies.

[0055] External factors affecting brightness can be categorized into foreign objects (including camera and screen foreign objects), abnormal camera parameters, and light leakage. Foreign objects and abnormal camera parameters typically cause a decrease in brightness in certain areas, making them easier to detect at high grayscale levels (32-255). Light leakage, on the other hand, usually causes an increase in brightness in certain areas, making it easier to detect at low grayscale levels (0-16). Target parameter values ​​can be generated in different ways based on the category of brightness-influencing factors.

[0056] See Figure 3 , Figure 3 This is a flowchart illustrating another embodiment of the anomaly detection method of this application. This detection method can determine the presence of foreign objects in the camera or differences in camera parameters, leading to abnormal brightness compensation. The method includes the following steps:

[0057] S210: Obtain the first brightness compensation value corresponding to multiple first pixel units in the first image, wherein the first image is obtained by the camera taking a picture of the first panel at the first gray level.

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

[0059] S220: Divide the area where multiple first pixel units are distributed in the first image into multiple first regions.

[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 at the same position as the first region, and determine the target parameter value corresponding to the first region based on 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 in the second region.

[0062] In this context, 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 capturing the second panel under the first grayscale. The second panel is the previous detected panel of the first panel. Furthermore, 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 is.

[0063] In actual testing, multiple display panels are typically tested sequentially using the same equipment. If foreign objects or other abnormalities appear on this equipment, the brightness compensation at the same location on each display panel will be abnormal after the foreign object is detected. This step compares the brightness compensation values ​​of the same area on the first panel currently being tested and the previously tested second panel. The second brightness compensation value is obtained using the same method and under the same conditions as the first brightness compensation value: the first and second images are obtained at the same grayscale, the display panels emit the same color light, the number of first pixel units in the first area is the same as the number of second pixel units in the second area, and the position of the first area in the first image is the same as the position of the second area in the second image. The target parameter value characterizes the degree of change of the first brightness compensation value of the first area compared to the second brightness compensation value at the same location (i.e., the second area) on the previous panel. The smaller the degree of change, the larger the target parameter value. Furthermore, since the first and second brightness compensation values ​​are obtained at the same grayscale, a smaller degree of change in the brightness compensation value indicates a smaller degree of change in the brightness value of that area.

[0064] S240: In response to any target parameter value corresponding to the first region being greater than the first parameter threshold, it is determined that the brightness compensation of 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 value of the same area of ​​two consecutive display panels changes only slightly, indicating that there is a foreign object blocking the light in the fixed area or that the camera parameters are abnormal. Subsequently, an alarm can be triggered to prompt engineers to investigate the cause.

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

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

[0068] Specifically, the absolute value of the difference in brightness compensation values ​​is calculated for each first pixel unit in the first region. For example, if 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 on the previous display panel is calculated, meaning there are 25 absolute values ​​in the first region.

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

[0070] In one embodiment, when the first region has 25 first pixel units, the target parameter value is the ratio of the number of absolute values ​​less than the difference threshold among the 25 to 25. Specifically, the difference threshold can be a fixed value, such as 3, 4, 5, etc., or it can be adjusted according to the first gray level. The difference threshold and the first gray level can be positively correlated; for example, when the first gray level is 224, the difference threshold is 5; when the first gray level is 128, the difference threshold is 4; when the first gray level is 32, the difference threshold is 3, and so on. Specifically, the range of the first parameter threshold is 40%-100%.

[0071] To facilitate understanding, examples and references are provided below. Figure 5 Explain the method for obtaining the target parameter value:

[0072] Taking a first gray level of 224, an interpolation threshold of 5, and a first parameter threshold of 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 value stored in the memory is retrieved. 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 by subtracting the values ​​in (b) and (a) to obtain the second brightness compensation value. Figure 5 In diagram (c), the difference between the first and second brightness compensation values ​​is shown, with differences less than 5 marked. The target parameter value is calculated for each first region, i.e., the number of differences less than 5 in each first region of diagram (c) is calculated and divided by 25 (the total number of differences in each first region), to obtain... Figure 5 Figure (d) shows the ratio of the number of differences with an absolute value less than 5 in each first region to 25. It can be seen from this figure that two first regions (shown in dashed boxes) have a ratio greater than 50% (64% and 60% respectively). This indicates that there are two first regions in the first image whose corresponding target parameter values ​​are greater than the difference threshold. It can be determined that at least two regions on the first panel correspond to locations with camera foreign objects or parameter anomalies, leading to abnormalities in subsequent brightness compensation.

[0073] In other embodiments, the target parameter values ​​corresponding to the first region can be calculated sequentially, and it can be 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 region is calculated. If the target parameter value is greater than the difference threshold, the calculation is stopped, and it is determined that the brightness compensation of the first panel is abnormal. This method has higher detection efficiency.

[0074] See Figure 6 , Figure 6 This is a flowchart illustrating another embodiment of the anomaly detection method of this application. This detection method can identify problems such as foreign objects on the screen, foreign objects in the camera, or differences in camera parameters, leading to abnormal brightness compensation. The method includes the following steps:

[0075] S310: Obtain the first brightness compensation value corresponding to multiple first pixel units in the first image, wherein the first image is obtained by the camera taking a picture of the first panel in the first gray level.

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

[0077] S320: Divide the area where multiple first pixel units are distributed in the first image into multiple first regions.

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

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

[0080] This target parameter value is used to characterize the degree of brightness compensation in the first region.

[0081] S340: In response to the difference between the target parameter values ​​corresponding to any two adjacent first regions 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 regions 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 has occurred by calculating the difference between the target parameter values ​​of any two adjacent first regions and then comparing the difference with the second parameter threshold. Since the brightness change of the screen itself is usually gradual, the change between adjacent regions is small, while foreign objects on the screen, foreign objects in the camera, or parameter abnormalities usually cause a large change in the edge brightness of the abnormal area. When the ratio of the target parameter values ​​corresponding to any two adjacent first regions is outside the range of the second parameter threshold, it indicates that the brightness compensation between the aforementioned first region and the adjacent first regions has a sudden change. This can determine that the position corresponding to the first region of the first panel has the aforementioned external influencing factors, causing the subsequent brightness compensation to be abnormal. Subsequently, an alarm can be triggered to prompt engineers to investigate the cause.

[0082] To facilitate understanding, examples and references are provided below. Figure 7 Explain the method for obtaining the target parameter value:

[0083] Continuing with the example of a first grayscale value of 224, first obtain the value in the following way: Figure 7 The absolute value of the first brightness compensation value corresponding to the first image shown in (a) is used to calculate the average of 25 absolute values ​​for each first region, resulting in... Figure 7 In (b), for each first region in (b), divide the average value corresponding to the current first region by the average value corresponding to the first region to its right, to obtain... Figure 7 As shown in (c), the ratio of the average values ​​can be seen from the figure. There are four first regions (shown by dashed boxes) whose ratios exceed 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 regions has changed abruptly. It can be determined that the first panel has screen foreign objects, camera foreign objects or abnormal parameters.

[0084] In other embodiments, the target parameter values ​​corresponding to two adjacent first regions can be calculated sequentially, taking the first region as a unit. It can then be determined whether the ratio of the two adjacent target parameter values ​​exceeds the range of a second parameter threshold. If the ratio is within the range, the ratio corresponding to the next set of first regions is calculated. If the ratio exceeds the range of the second parameter threshold, the calculation is stopped, indicating an anomaly in the brightness compensation of the first panel. This method has higher detection efficiency. Furthermore, adjacent first regions can be arranged horizontally or vertically, and the numerator and denominator of the ratio can be interchanged; this application does not impose specific limitations.

[0085] See Figure 8 , Figure 8 This is a flowchart illustrating another embodiment of the anomaly detection method of this application. This detection method can identify a light leakage problem, leading to abnormal brightness compensation. The method includes the following steps:

[0086] S410: Same as step S110, since light leakage will cause local brightness to be too high, the first gray level is less than or equal to 16, that is, the test is carried out at a low gray level.

[0087] S420: Same as step S120, and will not be described again here.

[0088] S431: Determine the median value of the first brightness compensation value based on the first brightness compensation values ​​corresponding to multiple first pixel units.

[0089] Specifically, because the test is conducted at low grayscale, the variation in brightness compensation values ​​is relatively small outside of the light leakage area, and the light leakage area usually occupies a small proportion of the entire area. Therefore, the median value of the first brightness compensation value usually corresponds to the brightness compensation value at 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 excluding the light leakage area.

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

[0091] Specifically, each first pixel unit corresponds to a ratio, which 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 the target parameter value corresponding to the first region based on the ratio corresponding to the first pixel unit in the first region. 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.

[0093] Specifically, the proportion of ratios exceeding a ratio threshold in the first region is determined, and this proportion is defined as the target parameter value for the first region. The target parameter value characterizes the degree of deviation in brightness compensation of the first region; the larger the target parameter value, the greater the deviation in brightness compensation value of the first region. When the first region has 20 first pixel units, the target parameter value is the ratio of the number of ratios greater than the ratio threshold among the 20 ratios to 20. Specifically, the ratio threshold can be a fixed value, such as 8, 10, 12, etc. In other embodiments, the number of ratios exceeding the ratio threshold in the first region can also be determined, and this number can be defined as the target parameter value for the first region.

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

[0095] Specifically, the threshold for the third parameter 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 light leakage.

[0097] To facilitate understanding, examples and references are provided below. Figure 9 Explain the method for obtaining the target parameter value:

[0098] Taking a first gray level of 16, a ratio threshold of 10, and a third parameter threshold of 50% as an example, firstly, obtain the following... Figure 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 first brightness compensation values ​​is 0.531095. Then, each first brightness compensation value is divided by this median value to obtain the result shown in (a). Figure 9 The ratios shown in (b) are then used. 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 identified), and this ratio is used as the target parameter value to obtain... Figure 9 The target parameter values ​​are shown in (c). As can be seen from this figure, one of the first regions (shown by the dashed box) has a proportion of 60%, which is greater than 50%. This indicates that the brightness of at least one of the first regions suddenly increases, confirming that light leakage occurred during the detection process.

[0099] In other embodiments, the target parameter value corresponding to the current first region can be calculated sequentially, and it can be 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 region is calculated. If it exceeds the third parameter threshold, the calculation is stopped, and it is determined that a light leakage anomaly has occurred during the detection process of the first panel. This method has higher detection efficiency.

[0100] Optionally, the method of this application further includes: sequentially using multiple different test gray levels as the first gray level, and then performing step S110. Specifically, the number of test gray levels is greater than or equal to 3, including 16, 128, and 224. Of course, in other embodiments, the number of test gray levels can be more, such as 10. In response to the determination that the brightness compensation of the first display panel is not abnormal under multiple test gray levels, it is finally determined that the brightness compensation of the first panel is not abnormal. Optionally, sub-pixels with red, green, and blue emission colors are lit up respectively under each test gray level, and tests are performed respectively. In response to the determination that the brightness compensation of the first display panel is not abnormal under each test, it is finally determined that the brightness compensation of the first panel is not abnormal.

[0101] See Figure 10 , Figure 10 This is a schematic diagram of a display device according to 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, and the processor 112 implements the anomaly detection method in the present application by executing the program data in the memory.

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

[0103] See Figure 11 , Figure 11This is a schematic diagram illustrating one embodiment of the computer-readable storage medium of this application. The computer-readable storage medium 120 of this application embodiment stores program instructions 121, which, when executed, implement the anomaly detection method provided in this application. The program instructions 121 can form a program file and be stored in the aforementioned computer-readable storage medium 120 in the form of a software product, so that a computer device (which may be a personal computer, server, or network device, etc.) can execute all or part of the steps of the methods of various embodiments of this application. The aforementioned computer-readable storage medium 120 includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, or terminal devices such as computers, servers, mobile phones, and tablets.

[0104] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0105] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0106] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus implementations described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or units may be electrical, mechanical, or other forms.

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

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0109] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0110] The above are merely embodiments of this application and do not limit the scope of this patent application. Any equivalent structural or procedural changes made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. An anomaly detection method, characterized in that, The method includes: Obtain first brightness compensation values ​​corresponding to multiple first pixel units in a first image, wherein the first image is obtained by a camera capturing a first panel at a first grayscale level; The region where the plurality of first pixel units are distributed in the first image is divided into a plurality of first regions; Based on the first brightness compensation value corresponding to the plurality of first pixel units, a target parameter value corresponding to each first region is generated respectively; Based on the target parameter values ​​corresponding to multiple first regions, it is determined whether the brightness compensation of the first panel is abnormal; wherein, The step of generating target parameter values ​​corresponding to each of the first regions based on the first brightness compensation values ​​corresponding to the plurality of first pixel units includes: For each of the first regions, a second region in the second image is determined that is at the same position as the first region. Based on 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 in the second region, the target parameter value corresponding to the first region is determined. The second pixel unit corresponding to the first pixel unit is at the same position in the second region as the first pixel unit is at the same position in the first region. The second image is obtained by the camera capturing a second panel at the first grayscale. The second panel is the previous detected panel of the first panel. 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 based on the target parameter values ​​corresponding to the plurality of first regions includes: In response to any target parameter value corresponding to the first region being greater than a first parameter threshold, it is determined that the brightness compensation of the first panel is abnormal; or, The step of generating target parameter values ​​corresponding to each of the first regions based on the first brightness compensation values ​​corresponding to the plurality of first pixel units includes: For each of the first regions, based on the first brightness compensation value of the first pixel unit in the first region, the absolute value of the average, median or mode of the first brightness compensation value is calculated to obtain the target parameter value corresponding to the first region. And, the step of determining whether the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to the plurality of first regions includes: In response to the difference between the target parameter values ​​corresponding to any two adjacent first regions exceeding the range of the second parameter threshold, it is determined that the brightness compensation of the first panel is abnormal; or, The step of generating target parameter values ​​corresponding to each of the first regions based on the first brightness compensation values ​​corresponding to the plurality of first pixel units includes: Based on the first brightness compensation values ​​corresponding to multiple first pixel units, determine the median value of the first brightness compensation value; For each first pixel unit, the ratio of the first brightness compensation value to the median value of the first pixel unit is calculated to obtain the ratio corresponding to the first pixel unit; For each of the first regions, the target parameter value corresponding to the first region is determined based on 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 the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to the plurality of first regions includes: In response to any target parameter value corresponding to the first region being greater than a third parameter threshold, it is determined that the brightness compensation of the first panel is abnormal.

2. The anomaly detection method according to claim 1, characterized in that, The method further includes: At the first grayscale, multiple sub-pixels in the first panel whose emission color is the target color are illuminated; The camera is controlled to take a picture of the first panel to obtain the first image.

3. The anomaly detection method according to claim 2, characterized in that, The target color includes red, green, or blue.

4. The anomaly detection method according to claim 1, characterized in that, The first gray level is greater than or equal to 32.

5. The anomaly detection method according to claim 1, characterized in that, The step of basing the first brightness compensation value of the first pixel unit in the first region on the second brightness compensation value of the corresponding second pixel unit in the second region at the first grayscale includes: Calculate the absolute value of the brightness difference between the first brightness compensation value of the first pixel unit in the first region and the second brightness compensation value of the corresponding second pixel unit in the second region to obtain multiple absolute values ​​corresponding to the first region; Determine the proportion of absolute values ​​less than a difference threshold among the plurality of absolute values ​​corresponding to the first region, and determine the proportion as the target parameter value corresponding to the first region.

6. The anomaly detection method according to claim 5, characterized in that, The first parameter threshold ranges from 40% to 100%.

7. 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 a difference greater than a second parameter threshold between any two adjacent target parameter values ​​of the first region includes: In response to the ratio of the target parameter values ​​corresponding to any two adjacent first regions being outside the range of the second parameter threshold, it is determined that the brightness compensation of the first panel is abnormal.

8. The anomaly detection method according to claim 7, characterized in that, The threshold value of the second parameter is in the range of 0.6-1.

5.

9. The anomaly detection method according to claim 1, characterized in that, The step of determining the target parameter value corresponding to the first region based on the ratio corresponding to the first pixel unit in the first region includes: Determine the proportion of the ratios that exceed a ratio threshold in the first region, and set the proportion as the target parameter value corresponding to the first region.

10. The anomaly detection method according to claim 9, characterized in that, The threshold value of the third parameter is in the range of 40%-100%.

11. The anomaly detection method according to claim 1, characterized in that, The method further includes: Multiple different test gray levels are sequentially used as the first gray level, and then the steps of obtaining the first brightness compensation value of multiple first pixel units in the first panel under the first gray level are executed, up to the step of determining whether the brightness compensation of the first panel is abnormal based on the target parameter values ​​corresponding to multiple first regions. If it is determined that the brightness compensation of the first panel is not abnormal under multiple test grayscale levels, then it is finally determined that the brightness compensation of the first panel is not abnormal.

12. The anomaly detection method according to claim 11, characterized in that, The number of test gray levels is greater than or equal to 3.

13. The anomaly detection method according to claim 11, characterized in that, The grayscale values ​​for the test grayscale include 16, 128, and 224.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that can be executed by a processor to implement the steps of the method as described in any one of claims 1-13.

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