Method for detecting display panel, electronic device and computer readable storage medium

Abstract

The application provides a display panel detection method, electronic equipment and a computer readable storage medium. Specifically, the detection method comprises: acquiring a display picture of a display panel; determining a display abnormal area from the display picture; dividing the display abnormal area into a plurality of sub-areas and determining a corresponding gray scale value variance of each sub-area; determining a fluctuation parameter based on the gray scale value variance; and determining a display abnormal reason of the display picture based on the fluctuation parameter. Specifically, the application determines the gray scale value variance of each sub-area by using the pixel gray scale value size distribution difference in the display abnormal area, obtains the fluctuation parameter of the entire display abnormal area, and then effectively and accurately detects the display abnormal reason of the display abnormal area by using the fluctuation parameter, thereby improving the detection level.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to a method for detecting a display panel, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Compared with LCD displays, OLED displays have advantages such as low power consumption, self-illumination, wide viewing angle and fast response speed, and are currently widely used in display fields such as mobile phones, tablets and TVs.

[0003] Currently, in the production of OLED display panels, fluctuations in the manufacturing process can cause various display defects in the displayed image.

[0004] For example, displays may exhibit defects such as bright spots or smudges. While bright spots can be repaired using remedial processes, smudges are generally irreparable. Taking a black screen as an example, a bright spot is caused by a single pixel emitting light within the same area, while a smudge is caused by multiple pixels emitting light within the same area. Current algorithms cannot accurately distinguish between bright spots and smudges during detection. Summary of the Invention

[0005] This application provides a method for detecting display panels, an electronic device, and a computer-readable storage medium, which can solve the problem that existing detection methods cannot accurately distinguish display defects in display panels.

[0006] To solve the above-mentioned technical problems, the first technical solution provided in this application is: a method for detecting a display panel, comprising: acquiring a display screen of the display panel; determining an abnormal display area from the display screen; dividing the abnormal display area into multiple sub-regions and determining the grayscale value variance corresponding to each sub-region; determining a fluctuation parameter based on the grayscale value variance; and determining the cause of the display abnormality of the display screen based on the fluctuation parameter.

[0007] In one embodiment, the step of determining the fluctuation parameter based on the grayscale value variance includes: determining the maximum and minimum grayscale value variances among the grayscale value variances corresponding to multiple sub-regions, and obtaining the fluctuation parameter using the formula (maximum grayscale value variance - minimum grayscale value variance) / (maximum grayscale value variance + minimum grayscale value variance); or, determining the maximum and minimum grayscale value variances among the grayscale value variances corresponding to multiple sub-regions, and obtaining the fluctuation parameter using the formula (maximum grayscale value variance - minimum grayscale value variance) / (maximum grayscale value variance); or, determining the maximum and minimum grayscale value variances among the grayscale value variances corresponding to multiple sub-regions, and obtaining the fluctuation parameter using the formula (maximum grayscale value variance - minimum grayscale value variance) / (average of all grayscale value variances in the grayscale value variance set).

[0008] In one embodiment, the step of determining the cause of the display abnormality based on the fluctuation parameter includes: in response to the value of the fluctuation parameter being within a first preset range, determining that the cause of the display abnormality is a bright spot defect; in response to the difference of the fluctuation parameter being within a second preset range, determining that the cause of the display abnormality is a bright spot defect; wherein the first preset range and the second preset range are of different sizes.

[0009] In one embodiment, the step of determining the abnormal display area from the display screen includes: obtaining the grayscale values ​​corresponding to all pixels in the display screen; determining abnormal pixels based on the grayscale values ​​of the pixels; and determining the abnormal display area based on the abnormal pixels.

[0010] In one embodiment, the step of determining the display abnormal region based on the abnormal pixels includes: defining the region including all the abnormal pixels as the display abnormal region.

[0011] In one embodiment, the step of defining the region including all the abnormal pixels as the display abnormal region includes: causing a portion of the abnormal pixels to be located on the boundary of the display abnormal region; preferably, the display abnormal region is a polygon, and each side of the polygon has at least one abnormal pixel; preferably, the display abnormal region is a rectangle.

[0012] In one embodiment, before acquiring the display screen of the display panel, the method further includes: controlling the display panel to display a black screen or a white screen, determining a first preset grayscale value based on the display panel displaying a black screen, or determining a second preset grayscale value based on the display panel displaying a white screen; the step of determining abnormal pixels based on the grayscale value of the pixels includes: in response to the display panel displaying a black screen, determining that the pixels with grayscale values ​​greater than the first preset grayscale value are abnormal pixels; or, in response to the display panel displaying a white screen, determining that the pixels with grayscale values ​​less than the second preset grayscale value are abnormal pixels.

[0013] In one embodiment, the step of dividing the display abnormality area into multiple sub-regions includes: uniformly dividing the number of pixels in the display abnormality area to obtain multiple sub-regions, such that the number of pixels in each sub-region is the same; preferably, the multiple sub-regions have the same shape.

[0014] To solve the above-mentioned technical problems, the second technical solution provided by this application is: to provide an electronic device, including a processor and a memory connected together, wherein the memory stores computer program instructions, and when the processor executes the computer program instructions, it implements the steps of the detection method as described in any of the above claims.

[0015] To solve the above-mentioned technical problems, the third technical solution provided by this application is: to provide a computer-readable storage medium storing program data thereon, wherein the program data, when executed by a processor, implements the steps of the detection method as described in any of the above claims.

[0016] Unlike existing technologies, the beneficial effect of this application lies in the following: the display panel detection method provided includes: acquiring the display screen of the display panel; determining abnormal display areas from the display screen; dividing the abnormal display areas into multiple sub-regions and determining the grayscale value variance corresponding to each sub-region; determining fluctuation parameters based on the grayscale value variance; and determining the cause of the display screen abnormality based on the fluctuation parameters. Specifically, this application utilizes the differences in pixel grayscale value distribution among the sub-regions within the abnormal display area to determine the grayscale value variance of each sub-region to obtain the fluctuation parameters of the entire abnormal display area. Furthermore, the fluctuation parameters can be used to effectively and accurately detect and classify the cause of the abnormal display in the abnormal display area, thereby improving the detection level. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein:

[0018] Figure 1 A schematic flowchart of an embodiment of the display panel detection method provided in this application;

[0019] Figure 2 A schematic flowchart of another embodiment of the display panel detection method provided in this application;

[0020] Figure 3 for Figure 1 or Figure 2 A flowchart illustrating an embodiment of step S2;

[0021] Figure 4 A grayscale value diagram of each pixel of a display panel provided in this application when displaying a black screen;

[0022] Figure 5 A schematic diagram of a module of an embodiment of the provided electronic device;

[0023] Figure 6 A schematic diagram of a module of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0024] The terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movement of components in a specific posture (as shown in the figures). If the specific posture changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0027] The applicant discovered the following flaws in the existing detection algorithm:

[0028] Taking a black screen on a display panel as an example, the brightness of defective light-emitting pixels is not fixed, which causes a large halo to appear when detecting bright spots. Existing detection algorithms may identify these bright spots as bright spots. Since bright spots cannot be repaired, these defective products are wasted, increasing the manufacturer's costs.

[0029] Alternatively, when detecting bright spots with low brightness, some defective pixels may not show a significant difference in brightness compared to normal pixels. This could lead existing detection algorithms to misclassify bright spots as bright spots, resulting in missed detections of defective pixels during product repair, causing abnormal client quality, impacting user experience and product reputation.

[0030] To solve the above problems, see [link to relevant documentation]. Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the display panel detection method provided in this application. Specifically, this application provides a display panel detection method, including:

[0031] Step S1: Obtain the display screen of the display panel.

[0032] The displayed screens include, but are not limited to: preset white screen, preset black screen, preset red screen, preset blue screen, and preset green screen. Different displayed screens are used to detect different types of defects.

[0033] In some methods, the display screen of the display panel can be captured by a camera device, such as a photosensitive camera or an industrial camera (CCD camera or CMOS camera), and the image information of the display screen can be converted into digital information for subsequent calculation and processing.

[0034] In one embodiment, multiple cameras on the lighting device capture multiple display images from the display panel from multiple angles. Multi-angle acquisition ensures comprehensiveness and reliability of the detection. The multiple display images are then converted into digital information and sent to a relevant processing module for image processing and analysis. The lighting device may integrate the relevant processing module, or the lighting device and the relevant processing device may be independently configured and coupled; this is not limited here.

[0035] See Figure 2 , Figure 2 A flowchart illustrating another embodiment of the display panel detection method provided in this application.

[0036] In one embodiment, before acquiring the display screen of the display panel, the method further includes:

[0037] Step S01: Control the display panel to display a black screen or a white screen, and determine a first preset grayscale value based on the display panel displaying a black screen, or determine a second preset grayscale value based on the display panel displaying a white screen.

[0038] Specifically, this embodiment is mainly used to detect defects in the display panel, such as bright spots or bright patches, and to control the display panel to display a black screen or a white screen, which is more conducive to the detection of this type of defect.

[0039] Of course, in other embodiments, if it is necessary to detect other types of defects, the display panel can be controlled to display a red, green, or blue image, etc., which is not limited here.

[0040] When the control panel displays a black screen, it can control the grayscale values ​​of all pixels to be the same or different, and to be less than a first preset grayscale value. For example, the first preset grayscale value includes, but is not limited to, 10, 20, 30, etc., and can be designed according to actual needs.

[0041] When the control panel displays a white screen, it can control the grayscale values ​​of all pixels to be the same or different, and to be greater than the second preset grayscale value. For example, the second preset grayscale value includes, but is not limited to, 230, 240, 250, etc., and can be designed according to actual needs.

[0042] Step S2: Identify the abnormal display area from the display screen.

[0043] Specifically, the relevant processing module can extract grayscale values ​​from all pixels in the display panel based on the image information collected by the lighting device, thereby determining abnormal display areas based on the grayscale values.

[0044] See Figure 3 and Figure 4 , Figure 3 for Figure 1 or Figure 2 A flowchart illustrating an embodiment of step S2; Figure 4 This is a grayscale value diagram of each pixel in an embodiment of the display panel provided in this application when displaying a black screen.

[0045] In one embodiment, the step of determining an abnormal display area from the display screen includes:

[0046] Step S21: Obtain the grayscale values ​​corresponding to all pixels in the display screen.

[0047] Among them, the relevant processing module can extract the grayscale values ​​of each pixel in the display panel based on the image captured by the lighting device.

[0048] Step S22: Determine abnormal pixels based on the grayscale value of the pixels.

[0049] In one embodiment, in response to the display panel displaying a black screen, pixels with grayscale values ​​greater than a first preset grayscale value are determined to be abnormal pixels.

[0050] Understandably, when the lighting device controls the preset grayscale value of all pixels in the display panel to be less than 60, so that the display panel displays a black screen, if the relevant processing module obtains a grayscale value greater than 60 for some pixels, then pixels with a grayscale value greater than 20 are determined to be abnormal pixels. For example... Figure 4 As shown, the display area includes multiple arrayed pixels, with each box representing a pixel. Abnormal pixels are represented by gray boxes, and normal pixels are represented by white boxes.

[0051] In one embodiment, in response to the display panel displaying a white screen, pixels with grayscale values ​​less than a second preset grayscale value are determined to be abnormal pixels.

[0052] Understandably, when the lighting device controls all pixels in the display panel to have a preset grayscale value greater than 200, so that the display panel displays a white image, if the relevant processing module obtains a grayscale value less than 200 for some pixels, then the pixels with a grayscale value less than 200 are determined to be abnormal pixels. (Not shown in the figure)

[0053] Step S23: Determine the display abnormal area based on the abnormal pixels.

[0054] Specifically, the abnormal area can be determined based on the location and distribution of abnormal pixels.

[0055] In one embodiment, the region that includes all abnormal pixels is defined as the display abnormal region.

[0056] The shape of the abnormal area can be, but is not limited to, rectangles, rhombuses, circles, or irregular shapes, as long as it can include all abnormal pixels.

[0057] In some implementations, to reduce the computational burden on related processing modules, the abnormal display area is divided into regular graphics.

[0058] In one embodiment, the step of defining the region including all abnormal pixels as the display abnormal region includes:

[0059] This causes some abnormal pixels to be located on the boundary of the display abnormal area.

[0060] Understandably, given that the abnormal display area includes all abnormal pixels, placing some abnormal pixels on the boundary of the abnormal display area can minimize the area covered by the abnormal display area, thereby excluding normal pixels from the abnormal display area as much as possible. This is beneficial for improving the accuracy of subsequent data processing and reducing the computational burden on the device.

[0061] In one embodiment, the abnormal display area is set as a polygon, such as a rectangle, rhombus, pentagon, hexagon, etc., and each side of the polygon has at least one abnormal pixel.

[0062] In one embodiment, the abnormal display area is set as a rectangle, and each of the four sides of the rectangle has at least one abnormal pixel.

[0063] like Figure 4 As shown, the specific implementation method can be to determine that the grayscale value in the display panel is greater than a first preset value (such as...). Figure 4 For abnormal pixels with a first preset value of 60, two first external tangent lines are drawn vertically for the leftmost and rightmost abnormal pixels on the display panel, and two second external tangent lines are drawn horizontally for the topmost and bottommost abnormal pixels on the display panel; a rectangular abnormal display area is formed based on the two first external tangent lines and the two second external tangent lines.

[0064] Step S3: Divide the abnormal area into multiple sub-regions and determine the variance of the grayscale value corresponding to each sub-region.

[0065] Specifically, according to the preset division rules, the relevant processing module can divide the abnormal display area into multiple sub-regions, and determine the variance of the grayscale value corresponding to each sub-region based on the grayscale value of all pixels in each sub-region.

[0066] For example, according to the preset division rules, the relevant processing module can divide the abnormal display area into 4 sub-regions, each sub-region including multiple pixels. The relevant processing module further calculates the grayscale value variance of all pixels in the 4 sub-regions respectively, and obtains four grayscale value variances Stdeva_A, Stdeva_B, Stdeva_C and Stdeva_D.

[0067] The shapes of the multiple sub-regions can be the same or different, and the number of pixels contained in each sub-region can be the same or different.

[0068] In one embodiment, the step of dividing the abnormal display area into multiple sub-regions includes:

[0069] The number of pixels in the abnormal display area is evenly divided to obtain multiple sub-regions, so that the number of pixels in each sub-region is the same.

[0070] Provided that the number of pixels in each sub-region is the same, the shape of each sub-region can be set to be the same, partially the same, or completely different. The shape of each sub-region includes, but is not limited to, rectangles, rhombuses, circles, or irregular shapes.

[0071] In one embodiment, multiple sub-regions have the same shape to facilitate division and reduce the computational burden on related processing devices. For example... Figure 4 As shown, the abnormal area is divided into four sub-regions, each of which is rectangular in shape and contains the same number of pixels.

[0072] In one embodiment, there may be overlapping portions between the sub-regions. For example, if the display abnormality area includes 9 columns of pixels, and the display abnormality area is to be divided into two sub-regions of the same shape and size, then the first sub-region includes columns 1 to 5 of pixels, and the second sub-region includes columns 5 to 9 of pixels.

[0073] Step S4: Determine the fluctuation parameter β based on the variance of the grayscale values.

[0074] Specifically, the relevant processing module calculates the fluctuation parameter β of the abnormal area based on the variance of the grayscale values ​​of each sub-region.

[0075] In one embodiment, the step of determining the fluctuation parameter β based on the variance of grayscale values ​​includes:

[0076] Determine the maximum and minimum grayscale variances among the grayscale variances corresponding to multiple sub-regions, and obtain the fluctuation parameter β using the formula (maximum grayscale variance - minimum grayscale variance) / (maximum grayscale variance + minimum grayscale variance).

[0077] For example, taking four grayscale variances Stdeva_A, Stdeva_B, Stdeva_C, and Stdeva_D as examples, calculate the maximum grayscale variance to obtain Stdeva_Max, calculate the minimum grayscale variance to obtain Stdeva_Min, and use the fluctuation parameter β formula β=(Stdeva_Max-Stdeva_Min) / (Stdeva_Max+Stdeva_Min) to calculate the fluctuation parameter β.

[0078] In another embodiment, the step of determining the fluctuation parameter β based on the grayscale value variance includes:

[0079] Determine the maximum and minimum grayscale variances among the grayscale variances corresponding to multiple sub-regions, and obtain the fluctuation parameter β using the formula (maximum grayscale variance - minimum grayscale variance) / (maximum grayscale variance).

[0080] For example, taking four grayscale variances Stdeva_A, Stdeva_B, Stdeva_C, and Stdeva_D as examples, calculate the maximum grayscale variance to obtain Stdeva_Max, calculate the minimum grayscale variance to obtain Stdeva_Min, and use the fluctuation parameter β formula β=(Stdeva_Max-Stdeva_Min) / Stdeva_Max to obtain the fluctuation parameter β.

[0081] In another embodiment, the step of determining the fluctuation parameter β based on the variance of grayscale values ​​includes:

[0082] Determine the maximum and minimum grayscale variances among the grayscale variances corresponding to multiple sub-regions, and obtain the fluctuation parameter β using the formula (maximum grayscale variance - minimum grayscale variance) / (average of all grayscale variances in the grayscale variance set).

[0083] For example, taking the variances of four grayscale values ​​Stdeva_A, Stdeva_B, Stdeva_C, and Stdeva_D as an example, calculate the maximum grayscale value variance to obtain Stdeva_Max, calculate the minimum grayscale value variance to obtain Stdeva_Min, and use the fluctuation parameter β formula β=(Stdeva_Max-Stdeva_Min) / ((Stdeva_A+Stdeva_B+Stdeva_C+Stdeva_D) / 4) to obtain the fluctuation parameter β.

[0084] Step S5: Determine the cause of the display abnormality based on the fluctuation parameter β.

[0085] In one embodiment, bright spots and blemishes are distinguished based on the fluctuation parameter β. The distinguishing value of the fluctuation parameter β needs to be set according to factors such as the product's pixel structure design and the brightness of the captured image; it can be obtained through prior experiments and calculations.

[0086] For example, when the display panel shows a black screen, if the value of the fluctuation parameter β is greater than the discrimination value, the defect in the abnormal display area is a bright spot defect. If the value of the fluctuation parameter β is less than the discrimination value, the defect in the abnormal display area is a bright spot defect.

[0087] In one embodiment, the step of determining the cause of display abnormalities based on the fluctuation parameter β includes:

[0088] If the value of the fluctuation parameter β is within the first preset range, the abnormality is determined to be due to a defective bright spot.

[0089] For example, if the value of the fluctuation parameter β is less than the discrimination value when the display panel shows a black screen, the defect in the abnormal display area is determined to be a bright spot defect.

[0090] If the difference in response to the fluctuation parameter β is within the second preset range, then the abnormality is determined to be due to poor brightness.

[0091] For example, if the value of the fluctuation parameter β is greater than the discrimination value when the display panel is displaying a black screen, the defect in the abnormal display area is determined to be a bright spot defect.

[0092] The first preset range and the second preset range have different sizes.

[0093] The following is an explanation using a set of experimental data.

[0094] When the display panel shows a black screen, the abnormal display area is a bright spot defect. The abnormal display area is divided into 4 sub-regions. The calculated variances of the grayscale values ​​of each sub-region are Stdeva_A: 86.2, Stdeva_B: 88.4, Stdeva_C: 83.1, and Stdeva_D: 87.2. According to the formulas for calculating the fluctuation parameter β, β1 is 0.024, β2 is 0.047, and β3 is 0.047.

[0095] When the display panel shows a black screen, the abnormal display area is a bright spot defect, and the abnormal display area is divided into 4 sub-regions. The grayscale variance of each sub-region is Stdeva_A: 53.4, Stdeva_B: 49.9, Stdeva_C: 77.1, and Stdeva_D: 87.5, respectively. According to the three formulas for calculating the fluctuation parameter β, β4 is 0.228, β5 is 0.429, and β6 is 0.561.

[0096] Based on the above data, it can be clearly seen that the difference in the value of the fluctuation parameter β corresponding to bright spot defects and bright spot defects is usually more than one order of magnitude. Using this feature, bright spot defects and bright spot defects can be well distinguished.

[0097] For example, based on the experimental data above, the discrimination value of the fluctuation parameter β can be set to 1.500. The first preset range can be less than 1.500, and the second preset range can be greater than 1.500. That is, when the value of the fluctuation parameter β is less than 1.500, the defect in the display abnormal area is determined to be a bright spot defect. When the value of the fluctuation parameter β is greater than 1.500, the defect in the display abnormal area is determined to be a bright spot defect.

[0098] Specifically, unlike existing technologies, some embodiments of this application utilize the differences in the distribution of pixel grayscale values ​​in each sub-region within the display abnormality area to determine the variance of grayscale values ​​in each sub-region to obtain the fluctuation parameter β of the entire display abnormality area. Furthermore, the fluctuation parameter β can be used to effectively and accurately detect and classify the cause of display abnormality in the display abnormality area, thereby improving the detection level.

[0099] See Figure 5 , Figure 5 This is a schematic diagram of a module of an embodiment of the provided electronic device. Specifically, this application also provides an electronic device 100, which includes a processor 10 and a memory 20 coupled to the processor 10; wherein, the memory 20 stores computer program instructions, and the processor 10 is used to execute the computer program instructions to implement the detection method provided in any of the above embodiments.

[0100] The processor 10 can also be referred to as a CPU (Central Processing Unit). The processor 10 may be an integrated circuit chip with signal processing capabilities. The processor 10 can 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, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0101] The memory 20 can be a memory module, TF card, etc., and can store all the information in the device's electronic equipment, including the input raw data, computer program, intermediate running results, and final running results. It stores and retrieves computer program instructions according to the location specified by the controller.

[0102] In some embodiments, the electronic device 100 includes, but is not limited to, the lighting device and related processing module described above.

[0103] See Figure 6 , Figure 6 This is a schematic diagram of a module of an embodiment of the computer-readable storage medium provided in this application. Specifically, this application also provides a computer-readable storage medium 200, which stores a program file 201 that can be executed to implement the steps of the detection method provided in any of the above embodiments.

[0104] The program file 201 may be stored in the aforementioned storage medium in the form of a software product, and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or controller (IC) to execute all or part of the steps of the methods of the various embodiments of this application.

[0105] 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. A method for detecting a display panel, characterized in that, include: Get the display screen of the display panel; Identify the abnormal display area from the displayed screen; The abnormal display area is divided into multiple sub-regions, and the variance of grayscale values ​​corresponding to each sub-region is determined. The fluctuation parameters are determined based on the variance of the grayscale values. The cause of the display abnormality is determined based on the fluctuation parameters; The step of determining the fluctuation parameter based on the variance of the grayscale values ​​includes: Determine the maximum and minimum grayscale value variances among the grayscale value variances corresponding to multiple sub-regions, and obtain the fluctuation parameter using the formula (maximum grayscale value variance - minimum grayscale value variance) / (maximum grayscale value variance + minimum grayscale value variance); or, Determine the maximum and minimum grayscale value variances among the grayscale value variances corresponding to multiple sub-regions, and obtain the fluctuation parameter using the formula (maximum grayscale value variance - minimum grayscale value variance) / (maximum grayscale value variance); or, The maximum and minimum grayscale variances among the grayscale variances corresponding to the multiple sub-regions are determined, and the fluctuation parameter is obtained using the formula (maximum grayscale variance - minimum grayscale variance) / (average of all grayscale variances in the grayscale variance set).

2. The detection method according to claim 1, characterized in that, The step of determining the cause of the display abnormality based on the fluctuation parameters includes: If the value of the fluctuation parameter is within a first preset range, the cause of the display abnormality is determined to be a defective bright spot. If the difference in the fluctuation parameter is within a second preset range, then the cause of the display abnormality is determined to be poor brightness. The first preset range and the second preset range have different sizes.

3. The detection method according to claim 1, characterized in that, The step of determining the abnormal display area from the display screen includes: Obtain the grayscale values ​​corresponding to all pixels in the displayed image; Abnormal pixels are determined based on the grayscale values ​​of the pixels; The abnormal display area is determined based on the abnormal pixels.

4. The detection method according to claim 3, characterized in that, The step of determining the display abnormal region based on the abnormal pixels includes: The region that includes all the abnormal pixels is defined as the display abnormal region.

5. The detection method according to claim 4, characterized in that, The step of defining the region including all the abnormal pixels as the display abnormal region includes: This causes some of the abnormal pixels to be located on the boundary of the display abnormal area.

6. The detection method according to claim 5, characterized in that, The abnormal display area is a polygon, and each side of the polygon has at least one abnormal pixel.

7. The detection method according to claim 5, characterized in that, The area displaying the abnormality is rectangular.

8. The detection method according to claim 3, characterized in that, Before acquiring the display screen of the display panel, the process also includes: Control the display panel to display a black screen or a white screen, and determine a first preset grayscale value based on the display panel displaying a black screen, or determine a second preset grayscale value based on the display panel displaying a white screen; The step of determining abnormal pixels based on the grayscale value of the pixel includes: In response to the display panel displaying the black screen, pixels with grayscale values ​​greater than the first preset grayscale value are determined to be abnormal pixels; or, In response to the display panel displaying the white screen, the pixels whose grayscale values ​​are less than the second preset grayscale value are determined to be abnormal pixels.

9. The detection method according to claim 1, characterized in that, The step of dividing the abnormal display area into multiple sub-regions includes: The number of pixels in the abnormal display area is uniformly divided to obtain multiple sub-regions, such that the number of pixels in each sub-region is the same.

10. The detection method according to claim 9, characterized in that, The multiple sub-regions have the same shape.

11. An electronic device, characterized in that, It includes a connected processor and a memory, the memory storing computer program instructions, and the processor executing the computer program instructions to implement the steps of the detection method as described in any one of claims 1-10.

12. A computer-readable storage medium storing program data thereon, characterized in that, When the program data is executed by the processor, it implements the steps of the detection method as described in any one of claims 1-10.

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