Mura identification method, device and equipment

Abstract

This invention discloses a method, apparatus, and device for identifying Mura (display area malfunction). The method includes: acquiring electrical data of each pixel obtained by performing an array test on a display panel; calculating the grayscale value of each pixel region during the array test based on the electrical data of each pixel, wherein the display panel includes multiple pixel regions, and each pixel region includes multiple pixels arranged in an array; and identifying Mura display areas in each pixel region based on the grayscale value of each pixel region. This invention solves the technical problem that existing technologies struggle to identify the fundamental influencing factors of Mura phenomena in display areas.

Description

Technical Field

[0001] The present invention belongs to the field of display technology, and in particular relates to a Mura identification method, device and equipment. Background Art

[0002] In the OLED (Organic Light-Emitting Diode) display panel industry, when the OLED display panel is working, there is uneven local display brightness, which causes various display traces, namely the Mura phenomenon. Therefore, it is necessary to identify the location where the Mura phenomenon occurs on the panel before leaving the factory, and then use various means to compensate for the brightness. At present, the existing Mura identification solutions are difficult to find the fundamental factors affecting the Mura phenomenon in the display area. Summary of the invention

[0003] The embodiments of the present invention provide a mura identification method, device and apparatus, which can solve the technical problem that it is difficult to find the fundamental influencing factors of the mura phenomenon in the display area in the prior art.

[0004] In a first aspect, a mura identification method is provided, comprising:

[0005] Acquiring electrical data of each pixel point obtained by performing array testing on the display panel;

[0006] Calculate the grayscale value of each pixel area during array testing according to the electrical data of each pixel point, the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array;

[0007] According to the grayscale value of each pixel area, a Mura display area in each pixel area is identified.

[0008] Optionally, according to the electrical data of each pixel point, the grayscale value of each pixel area during the array test is calculated, including:

[0009] Performing convolution processing on the electrical data of multiple pixel points in each pixel area respectively to obtain regional electrical data of each pixel area;

[0010] Obtaining an average value of the regional electrical data of each pixel region, and a maximum value and a minimum value in the regional electrical data of each pixel region;

[0011] According to the regional electrical data, maximum value, minimum value and average value of each pixel area, the grayscale value of each pixel area during the array test is calculated.

[0012] This solution provides effective electrical characteristic parameters for the subsequent identification of Mura display areas, helping to achieve quantitative identification of electrical Mura phenomena with high repeatability and accuracy.

[0013] Optionally, according to the regional electrical data, the maximum value, the minimum value and the average value of each pixel area, the grayscale value of each pixel area during the array test is calculated, including:

[0014] The grayscale value of each pixel area during array testing is calculated according to the following formula:

[0015]

[0016] in, is the grayscale value of pixel area A during array testing, I A is the regional electrical data of pixel area A, avg(I) is the average value, MAX(I) is the maximum value, and MIN(I) is the minimum value.

[0017] This solution obtains the regional electrical data of each pixel area through the electrical data of each pixel point of the display panel, and then converts it to obtain the grayscale value of each pixel area during the array test. Therefore, based on the grayscale value of each pixel area, the Mura display area can be identified from multiple pixel areas, thereby realizing electrical Mura identification with low interference.

[0018] Optionally, identifying a Mura display area in each pixel area according to a grayscale value of each pixel area includes:

[0019] Calculate the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale;

[0020] A pixel area where a target grayscale value is located is identified as a Mura display area, and the target grayscale value is a grayscale value where a Mura display rate exceeds a preset value.

[0021] This solution can accurately identify the Mura display position based on the grayscale value, so that the Mura phenomenon affected by the electrical factors of the array end can be directly identified, thereby solving the technical problem in the prior art that it is difficult to find the fundamental influencing factors of the Mura phenomenon in the display area, and can replace manual identification, can be quantified and executed, and improves the detection speed and accuracy.

[0022] Optionally, calculating the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale includes:

[0023] Calculate the absolute value of the difference between the grayscale value of each pixel area and the reference grayscale;

[0024] The Mura display rate of the grayscale value of each pixel area relative to the reference grayscale is calculated according to the following formula:

[0025]

[0026] Among them, g Ais the Mura display rate of pixel area A relative to the reference grayscale, is the absolute value of the difference between the grayscale value of pixel area A and the reference grayscale. This solution calculates the Mura display rate by setting the reference grayscale, and can obtain the probability of electrical Mura phenomenon display in each pixel area, providing a quantifiable parameter for subsequent Mura identification.

[0027] Optionally, the reference grayscale is an average grayscale calculated according to the grayscale values ​​of each pixel area, providing a reference specification for Mura identification.

[0028] Optionally, identifying a Mura display area in each pixel area according to a grayscale value of each pixel area includes:

[0029] According to the grayscale value of each pixel area, a grayscale image displayed by the display panel is simulated;

[0030] Identify mura display areas from grayscale images.

[0031] This solution achieves visual electrical Mura identification by simulating the grayscale image of the display panel. At the same time, the identification of electrical Mura is not affected by the vapor deposition material.

[0032] Optionally, the electrical data of each pixel point includes at least one of a voltage value, a current value and an accumulated charge amount during a charging and discharging process of each pixel point during array testing.

[0033] In a second aspect, a mura identification device is provided, including:

[0034] An acquisition module, used to acquire electrical data of each pixel point obtained by performing array testing on the display panel;

[0035] A calculation module, used to calculate the grayscale value of each pixel area during array testing according to the electrical data of each pixel point, the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array;

[0036] The identification module is used to identify the Mura display area in each pixel area according to the grayscale value of each pixel area.

[0037] In a third aspect, a mura identification device is provided. The mura identification device includes a memory, a processor, and a computer program stored in the memory and running on the processor. The computer program implements the steps of the mura identification method in the first aspect.

[0038] In a fourth aspect, a computer storage medium is provided, which, when executed by a processor, implements the steps of the mura identification method in the first aspect.

[0039] In a fifth aspect, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the steps of the mura identification method in the first aspect are implemented.

[0040] Compared with the prior art, the Mura identification method, device and equipment provided in the embodiments of the present application calculate the grayscale value of each pixel area during the array test based on the electrical data of each pixel point, and then identify the Mura display area in each pixel area based on the grayscale value of each pixel area. Because the parameters used to identify the Mura display area are directly read from the electrical data of each pixel point during the array test, it is not necessary to light up the display panel after the evaporation process to identify the Mura display area affected by the array end factors. Therefore, the Mura phenomenon affected by the array factors is directly distinguished, which solves the technical problem that the prior art is difficult to find the fundamental influencing factors of the Mura phenomenon in the display area, and can replace manual identification, can be quantified and executed, and improves the detection speed and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 is a schematic flow chart of a mura identification method according to an embodiment of the present invention.

[0043] Figure 2 Detailed flowchart of step S120 in the mura identification method according to another embodiment of the present invention.

[0044] Figure 3 FIG. 4 is a schematic block diagram of a Mura identification device according to an embodiment of the present invention.

[0045] Figure 4 4 is a schematic block diagram of a Mura identification device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The features and exemplary embodiments of various aspects of the present invention will be described in detail below. In the detailed description below, many specific details are proposed to provide a comprehensive understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by illustrating examples of the present invention.

[0047] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0048] At present, with the advancement of display technology, OLED (Organic Light-Emitting Diode) display panels have gradually become the mainstream development direction. The uneven local brightness display phenomenon of OLED (i.e., Mura phenomenon) is one of the problems that OLED development needs to focus on overcoming. However, due to the differences in the characteristics of TFT (Thin Film Transistor) and light-emitting units in different OLED display panels, the distribution, shape and form of Mura in the display panel are not fixed.

[0049] After long-term research, the inventor found that in order to achieve Mura identification, the relevant technology is mainly to use a lighting machine to light up a single screen to display image data after the OLED array process and evaporation process are completed, and then manually perform subjective identification. However, this Mura identification method has the following problems:

[0050] 1. Although relevant Mura identification personnel have received unified Mura display judgment training, there are large subjective differences between individuals and cannot be quantified. In addition, the visual effect of the human body will deteriorate as attention decreases, which can easily lead to over-detection or missed detection in Mura identification.

[0051] 2. The Mura identification method is to use a lighting machine to make the pixel area in the panel glow after the OLED array process and the evaporation process to achieve identification. Therefore, the Mura display area actually identified is affected by both the array factor and the evaporation material factor. It is difficult to distinguish whether the Mura display area is caused by the electrical factors of the array end or the Mura phenomenon caused by the evaporation material factor.

[0052] In summary, the mura identification method in the related art objectively has the problem of difficulty in finding the fundamental influencing factors of the mura phenomenon in the display area and low mura identification accuracy. In order to solve this technical problem, the inventor of this application explored and discovered the essential cause of electrical mura in the display panel array process based on the quality test of each pixel in the array test link.

[0053] It should be noted that in the related art, the OLED array test link mainly tests the amount of charge in the array circuit within a specified time, and then compares the amount of charge with the set upper limit line to realize a binary judgment on whether the circuit is normally connected or disconnected. The inventor of this application found that although this binary judgment can identify the quality of pixels, when the evaluation of the pixels is good, the electrical characteristics of each pixel are different, which can lead to different output currents of each pixel circuit, so that when the actual light is emitted, the display of different display areas of the display panel is different, resulting in the Mura phenomenon affected by the electrical factors of the array end (hereinafter referred to as "electrical Mura").

[0054] It can be seen that the essence of electrical Mura generated in the OLED array process is that after the array process is completed, the different current values ​​generated by the pixels in each row in each display panel after the same data signal is written. Therefore, after the OLED array test (Array Test) link, the electrical data of each pixel obtained by the array test equipment can be read, and Mura identification can be realized based on the electrical data. Starting from the essence of the occurrence of Mura affected by the electrical factors of the array end, electrical Mura identification is realized with the help of the electrical data obtained from the array test, so as to solve the technical problems of the difficulty in finding the fundamental influencing factors of the Mura phenomenon in the display area and the low accuracy of Mura identification in the prior art.

[0055] The following first introduces the Mura identification method of the embodiment of the present application.

[0056] See also Figure 1 In an optional example, the mura identification method includes:

[0057] S110, acquiring electrical data of each pixel point obtained by performing an array test on the display panel.

[0058] S120, calculating the grayscale value of each pixel area during array testing according to the electrical data of each pixel point. Specifically, the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array.

[0059] S130 , identifying a Mura display area in each pixel area according to the grayscale value of each pixel area.

[0060] The embodiment of the present application calculates the grayscale value of each pixel area during the array test based on the electrical data of each pixel point, and then identifies the Mura display area in each pixel area based on the grayscale value of each pixel area. Because the parameters used to identify the Mura display area are directly read from the electrical data of each pixel point during the array test, it is not necessary to light up the display panel after the evaporation process to achieve electrical Mura identification, so that electrical Mura identification is no longer affected by evaporation, that is, it directly distinguishes the Mura phenomenon affected by array-side factors, which solves the technical problem that the prior art is difficult to find the fundamental influencing factors of the Mura phenomenon in the display area, and can replace manual identification, can be quantified, and improves the detection speed and accuracy.

[0061] In some embodiments, in S110, the electrical data of each pixel can be read directly from the array test device, or the method can also be directly executed by the array test device. In other embodiments, the electrical data of each pixel reported by the array test device can also be read from the server. Exemplarily, the server can be an FTP server (File Transfer Protocol Server, File Transfer Protocol Server), and the electrical data of each pixel can be stored in the DFS (Distributed File System, Distributed File System) directory of the FTP server. When Mura identification is required, the electrical data of each pixel of the display panel at that time can be found and read from the DFS directory through the fast posting operation (Track Out) time in the OLED Manufacturing Execution System (MES).

[0062] It should be noted that the electrical data of each pixel point includes at least one of the voltage value, current value and accumulated charge amount of each pixel point during the charging and discharging process during the array test. Taking the electrical data as the accumulated charge amount as an example, the array test equipment can scan the display panel line by line, and then integrate the accumulated charge amount of each pixel point during the charging and discharging process measured in the array test link by sampling the charge amount of each pixel point, and the accumulated charge amount is the electrical data of the pixel point. Therefore, by extracting the electrical data of the pixel points of the entire display panel during the array test, the final Mura identification covers the entire display area, ensuring the data integrity of the Mura identification.

[0063] In some embodiments, the grayscale value of each pixel area in the display panel can be calculated based on the electrical data of each pixel point by a software program. For example, the software program can be implemented in a programming language such as Java or Python.

[0064] The pixel regions can be divided according to actual needs. Each display panel includes a plurality of pixel regions, the plurality of pixel regions do not overlap, and each pixel region includes a plurality of pixel points arranged in an array.

[0065] In some optional embodiments of the present application, the plurality of pixel regions may be divided according to the display region sizes of different display panels. For example, the display panel may be divided into 20*30 pixel regions.

[0066] Exemplarily, the display panel can be divided into 20*20 pixel areas, each pixel area includes n*n pixel points, n is an integer greater than or equal to 2, and the grayscale value of the corresponding pixel area can be obtained based on the electrical data of each pixel point in each pixel area.

[0067] See also Figure 2 In some optional examples, in S120, the process of calculating the grayscale value of each pixel area during the array test according to the electrical data of each pixel point may include:

[0068] S221, performing convolution processing on the electrical data of multiple pixel points in each pixel area respectively to obtain regional electrical data of each pixel area.

[0069] S222, obtaining an average value of the regional electrical data of each pixel region, and a maximum value and a minimum value of the regional electrical data of each pixel region.

[0070] S223, calculating the grayscale value of each pixel area during the array test according to the regional electrical data, the maximum value, the minimum value and the average value of each pixel area.

[0071] This example provides a method for obtaining the grayscale value of each pixel area during array testing based on the electrical data of each pixel point. It provides effective electrical characteristic parameters for the subsequent identification of Mura display areas and helps to achieve quantitative identification of electrical Mura phenomena with high repeatability and accuracy.

[0072] Among them, the convolution processing can be used to blur the electrical data of each pixel in the pixel area, thereby eliminating the display differences caused by a small number of electrical data deviations or bad pixels, achieving the uniformity of a single pixel area, and then helping to accurately find the phenomenon of local display unevenness of the display panel in the subsequent process.

[0073] The electrical data of a single pixel point may be expressed in a matrix form, and then the electrical data of all the pixels in a single pixel area may be added up in a matrix to obtain the regional electrical data of the single pixel area.

[0074] For example, the regional electrical data of the pixel region A may be calculated according to the following formula (1).

[0075]

[0076] Among them, I A is the regional electrical data of pixel area A, n∈N, N is the convolution value corresponding to the convolution processing, that is, the set of pixels in pixel area A, i A is the electrical data of a pixel in the pixel area A.

[0077] It should be noted that the regional electrical data corresponds to the type of electrical data of the pixel point, and represents the electrical data value after the electrical data of multiple pixel points in a single pixel area are homogenized. On this basis, the maximum and minimum values ​​can be found, and the average value of the regional electrical data of each pixel area can be calculated.

[0078] The grayscale value of each pixel area during the array test can be calculated by combining the maximum value, minimum value and average value obtained through the regional electrical data of each pixel area through formula (2).

[0079]

[0080] in, is the grayscale value of pixel area A during array testing, I A is the regional electrical data of pixel area A, avg(I) is the average value, MAX(I) is the maximum value, and MIN(I) is the minimum value.

[0081] In the example of the present application, the regional electrical data of each pixel area is obtained by the electrical data of each pixel point of the display panel, and then converted into the grayscale value of each pixel area during the array test. Therefore, the Mura display area can be identified from multiple pixel areas based on the grayscale value of each pixel area, thereby realizing electrical Mura recognition with low interference.

[0082] In an optional embodiment, in S130, the process of identifying the Mura display area in each pixel area according to the grayscale value of each pixel area during the array test can be to compare the grayscale value of each pixel area with the set specification, and select the pixel area where the grayscale value that does not meet the specification is located as the Mura display area.

[0083] Specifically, the set specification may be a reference grayscale, which is considered normal display grayscale data, and may be an average grayscale calculated based on the grayscale values ​​of each pixel area, or may be the median of the grayscale values ​​of each pixel area, etc. The grayscale value of each pixel area may be further compared with the reference grayscale, and the pixel area whose difference with the reference grayscale is far from the set threshold range may be considered as a mura display area.

[0084] The Mura display rate of the grayscale value of each pixel area relative to the reference grayscale can also be calculated, and the Mura display rate represents the probability of the electrical Mura phenomenon in each pixel area. The pixel area where the target grayscale value is located can be identified as the Mura display area, where the target grayscale value is the grayscale value where the Mura display rate exceeds the preset value. The preset value can be 90%, 88%, 92% or other values, and its specific value can be set according to the actual situation.

[0085] Specifically, the process of calculating the Mura display rate may include: respectively calculating the absolute value of the difference between the grayscale value of each pixel area and the reference grayscale; and calculating the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale according to formula (3).

[0086]

[0087] Among them, g A is the Mura display rate of pixel area A relative to the reference grayscale, is the absolute value of the difference between the grayscale value of the pixel area A and the reference grayscale.

[0088] In this embodiment, by setting a reference grayscale to calculate the Mura display rate, the probability of electrical Mura phenomenon display in each pixel area can be obtained, which helps to accurately identify the Mura display position based on the grayscale value, so that the Mura phenomenon affected by the electrical factors of the array end can be directly identified, thereby solving the technical problem in the prior art that it is difficult to find the fundamental influencing factors of the Mura phenomenon in the display area, and can replace manual identification, can be quantified and executed, and improves the detection speed and accuracy.

[0089] In another optional embodiment, in S130, a grayscale image displayed by the display panel may be simulated according to the grayscale value of each pixel area; and then the Mura display area may be identified from the grayscale image.

[0090] The process of simulating the grayscale image displayed by the above-mentioned display panel may include: inputting the grayscale value of each pixel area into the image processing program, and the image processing program performs a simulated output of the image. Among them, the image processing program can be a program that can process and output according to the grayscale value of each pixel area. Exemplarily, the image processing program can be implemented with the help of OpenCV, which is a cross-platform computer vision and machine learning software library. After obtaining the grayscale image, the software can capture the area with uneven local brightness display, and then identify the Mura display area.

[0091] The embodiment of the present application realizes visual electrical Mura recognition by simulating the grayscale image of the display panel, and the recognition of the electrical Mura is not affected by the vapor deposition material.

[0092] In order to enhance the accuracy of electrical Mura identification, the above-mentioned image output identification scheme can also be combined with the above-mentioned Mura identification scheme based on Mura display rate. With the help of image output identification, the Mura display area identified based on the Mura display rate is verified. Only when both schemes are verified, it is confirmed as a Mura display area. In this way, identification is performed from both image and program algorithm aspects, thereby improving the accuracy of electrical Mura identification.

[0093] In some optional examples of the present application, the above-mentioned image output recognition scheme and the aforementioned Mura recognition scheme based on Mura display rate can be verified as a Mura display area, that is, it is considered to be a Mura display area, and comprehensive Mura recognition can be achieved.

[0094] It is understandable that the mura identification method may further include sending a reminder message to the tester, such as sending an email to the tester, so that the tester can analyze and process the mura display area with the help of the monitoring system. If the mura display area is not identified, the production operation (such as tape-out, etc.) can continue.

[0095] Combined with the above Figure 1 to Figure 2 The Mura identification method according to the embodiment of the present invention is described in detail. Figure 3 , a Mura identification device according to an embodiment of the present invention is described in detail.

[0096] See also Figure 3 In one embodiment, the Mura identification device includes:

[0097] An acquisition module 310 is used to acquire electrical data of each pixel point obtained by performing an array test on the display panel;

[0098] The calculation module 320 is used to calculate the grayscale value of each pixel area during the array test according to the electrical data of each pixel point, and the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array;

[0099] The identification module 330 is used to identify the Mura display area in each pixel area according to the grayscale value of each pixel area.

[0100] Optionally, the calculation module 320 includes:

[0101] A processing unit, used to perform convolution processing on the electrical data of multiple pixel points in each pixel area respectively, to obtain regional electrical data of each pixel area;

[0102] An acquisition unit, used to acquire an average value of the regional electrical data of each pixel area, and a maximum value and a minimum value in the regional electrical data of each pixel area;

[0103] The first calculation unit is used to calculate the grayscale value of each pixel area during array testing according to the regional electrical data, maximum value, minimum value and average value of each pixel area.

[0104] Optionally, the first calculation unit is specifically configured to calculate the grayscale value of each pixel area during array testing according to the following formula:

[0105]

[0106] in, is the grayscale value of pixel area A during array testing, I A is the regional electrical data of pixel area A, avg(I) is the average value, MAX(I) is the maximum value, and MIN(I) is the minimum value.

[0107] Optionally, the identification module 330 includes:

[0108] A second calculation unit is used to calculate the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale;

[0109] The identification unit is used to identify a pixel area where a target grayscale value is located as a Mura display area, and the target grayscale value is a grayscale value whose Mura display rate exceeds a preset value.

[0110] Optionally, the second computing unit includes:

[0111] A first calculation subunit, used for respectively calculating the absolute value of the difference between the grayscale value of each pixel area and the reference grayscale;

[0112] The second calculation subunit is used to calculate the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale according to the following formula:

[0113]

[0114] Among them, g A is the Mura display rate of pixel area A relative to the reference grayscale, is the absolute value of the difference between the grayscale value of the pixel area A and the reference grayscale.

[0115] Optionally, the reference grayscale is an average grayscale calculated according to the grayscale values ​​of each pixel area.

[0116] Optionally, the identification module includes:

[0117] A simulation unit, used to simulate the grayscale image displayed by the display panel according to the grayscale value of each pixel area;

[0118] The identification unit is used to identify the Mura display area from the grayscale image.

[0119] Optionally, the electrical data of each pixel point includes at least one of a voltage value, a current value and an accumulated charge amount during a charging and discharging process of each pixel point during array testing.

[0120] Figure 4 The hardware structure diagram of the Mura identification device provided in the embodiment of the present application is shown. The Mura identification device may include a processor 401 and a memory 402 storing computer program instructions.

[0121] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0122] Memory 402 may include a large capacity memory for data or instructions. By way of example and not limitation, memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, memory 402 may include a removable or non-removable (or fixed) medium. In appropriate cases, memory 402 may be inside or outside of an integrated gateway disaster recovery device. In a specific embodiment, memory 402 is a non-volatile solid-state memory.

[0123] The memory 402 may include a read-only memory (ROM), a flash memory device, a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, an electrical, optical or other physical / tangible memory storage device. Thus, typically, the memory 402 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to the above aspects of the present disclosure.

[0124] The processor 401 implements any one of the mura identification methods in the above embodiments by reading and executing computer program instructions stored in the memory 402 .

[0125] In one example, the mura identification device may further include a communication interface 403 and a bus 410. Figure 4 As shown, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 410 and communicate with each other.

[0126] The communication interface 403 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0127] Bus 410 includes hardware, software, or both, coupling the components of the Mura identification device to each other. By way of example and not limitation, the bus may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industrial standard architecture (EISA) bus, a front-side bus (FSB), a hypertransport (HT) interconnect, an industrial standard architecture (ISA) bus, an infinite bandwidth interconnect, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus, or other suitable bus or a combination of two or more of these. Where appropriate, bus 410 may include one or more buses. Although the present application describes and illustrates a specific bus, the present application considers any suitable bus or interconnect.

[0128] The mura identification device can be based on the mura identification method to achieve the combination Figures 1 to 3 The mura identification method and device described.

[0129] In combination with the mura identification method in the above embodiments, the present application embodiment may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the mura identification methods in the above embodiments is implemented.

[0130] In addition, in combination with the mura identification method in the above embodiment, the embodiment of the present application can provide a computer program product for implementation. The computer program product stores computer program instructions; when the computer program instructions are executed by a processor, any one of the mura identification methods in the above embodiment is implemented.

[0131] It should be noted that the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0132] It should be understood that in the embodiment of the present invention, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0133] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A mura identification method, characterized in that: include: Acquiring electrical data of each pixel point obtained by performing array testing on the display panel; Calculating the grayscale value of each pixel area during array testing according to the electrical data of each pixel point, wherein the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array; Identifying a Mura display area in each of the pixel areas according to a grayscale value of each of the pixel areas; The step of calculating the grayscale value of each pixel area during array testing according to the electrical data of each pixel point includes: Performing convolution processing on the electrical data of the plurality of pixel points in each pixel area respectively to obtain regional electrical data of each pixel area; Obtaining an average value of the regional electrical data of each of the pixel regions, and a maximum value and a minimum value of the regional electrical data of each of the pixel regions; Calculating the grayscale value of each pixel area during array testing according to the regional electrical data of each pixel area, the maximum value, the minimum value and the average value; The step of calculating the grayscale value of each pixel region during array testing according to the regional electrical data of each pixel region, the maximum value, the minimum value, and the average value comprises: The grayscale value of each pixel area during array testing is calculated according to the following formula: in, is the grayscale value of pixel area A during array testing, I A is the regional electrical data of pixel area A, avg(I) is the average value, MAX(I) is the maximum value, and MIN(I) is the minimum value.

2. The method according to claim 1, characterized in that The step of identifying the Mura display area in each of the pixel areas according to the grayscale value of each of the pixel areas comprises: Calculating the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale; A pixel area where a target grayscale value is located is identified as the Mura display area, and the target grayscale value is a grayscale value at which the Mura display rate exceeds a preset value.

3. The method according to claim 2, characterized in that The calculating the Mura display rate of the grayscale value of each pixel area relative to the reference grayscale includes: Calculating the absolute value of the difference between the grayscale value of each pixel area and the reference grayscale respectively; The Mura display rate of the grayscale value of each pixel area relative to the reference grayscale is calculated according to the following formula: Among them, g A is the Mura display rate of pixel area A relative to the reference grayscale, is the absolute value of the difference between the grayscale value of the pixel area A and the reference grayscale.

4. The method according to claim 3, characterized in that The reference grayscale is an average grayscale calculated based on the grayscale values ​​of each of the pixel regions.

5. The method according to claim 1, characterized in that The step of identifying the Mura display area in each of the pixel areas according to the grayscale value of each of the pixel areas comprises: According to the grayscale value of each pixel area, simulating the grayscale image displayed by the display panel; The Mura display area is identified from the grayscale image.

6. The method according to claim 1, characterized in that The electrical data of each pixel point includes at least one of a voltage value, a current value, and an accumulated charge amount during the charging and discharging process of each pixel point during array testing.

7. A mura identification device, characterized in that: include: An acquisition module, used to acquire electrical data of each pixel point obtained by performing array testing on the display panel; A calculation module, used to calculate the grayscale value of each pixel area during array testing according to the electrical data of each pixel point, wherein the display panel includes a plurality of pixel areas, and each pixel area includes a plurality of pixel points arranged in an array; An identification module, used for identifying a Mura display area in each of the pixel areas according to a grayscale value of each of the pixel areas; The step of calculating the grayscale value of each pixel area during array testing according to the electrical data of each pixel point includes: Performing convolution processing on the electrical data of the plurality of pixel points in each pixel area respectively to obtain regional electrical data of each pixel area; Obtaining an average value of the regional electrical data of each of the pixel regions, and a maximum value and a minimum value of the regional electrical data of each of the pixel regions; Calculating the grayscale value of each pixel area during array testing according to the regional electrical data of each pixel area, the maximum value, the minimum value and the average value; The step of calculating the grayscale value of each pixel region during array testing according to the regional electrical data of each pixel region, the maximum value, the minimum value, and the average value comprises: The grayscale value of each pixel area during array testing is calculated according to the following formula: in, is the grayscale value of pixel area A during array testing, I A is the regional electrical data of pixel area A, avg(I) is the average value, MAX(I) is the maximum value, and MIN(I) is the minimum value.

8. A mura identification device, characterized in that: The mura identification device comprises a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the computer program executes the steps of the mura identification method according to any one of claims 1 to 6.

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