Data correction methods, apparatus, devices, readable storage media, and program products

Abstract

This application relates to a data correction method, apparatus, device, readable storage medium, and program product. The method includes: acquiring target brightness feature data corresponding to a target screen through an application device; acquiring brightness correction data corresponding to the target module based on the target module corresponding to the target screen; and correcting the target brightness feature data according to the brightness correction data and a correction strategy corresponding to the experimental equipment. This method can improve correction accuracy.

Description

Technical Field

[0001] This application relates to the field of optoelectronic technology, and in particular to a data correction method, apparatus, device, readable storage medium, and program product. Background Technology

[0002] During the manufacturing of monitor panels, uneven brightness may occur due to various reasons. Therefore, Demura technology was developed to correct the brightness data of the panel.

[0003] In related technologies, the Demura algorithm is usually designed by taking pictures of sample screens in the laboratory using laboratory cameras. Subsequently, in the production line, the brightness data of the screens produced on the production line is corrected based on the designed Demura algorithm and the cameras in the production line.

[0004] However, the above data correction methods suffer from poor accuracy. Summary of the Invention

[0005] Therefore, it is necessary to provide a data correction method, apparatus, device, readable storage medium, and program product that can improve the accuracy of correction in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a data correction method, including:

[0007] The target brightness feature data corresponding to the target screen is obtained through the application device;

[0008] Based on the target module corresponding to the target screen, obtain the brightness correction data corresponding to the target module;

[0009] Based on the brightness correction data and the corresponding correction strategy of the experimental equipment, the target brightness feature data is corrected.

[0010] In one embodiment, obtaining the brightness correction data corresponding to the target mode position includes:

[0011] The first brightness feature data corresponding to multiple first sample screens under the target mode is obtained by the application device, and the second brightness feature data corresponding to multiple first sample screens under the target mode is obtained by the experimental device.

[0012] Brightness correction data is obtained based on each first brightness feature data and each second brightness feature data.

[0013] In one embodiment, brightness correction data is obtained based on each first brightness feature data and each second brightness feature data, including:

[0014] For each first sample screen, calculate the ratio of the second brightness feature data to the first brightness feature data;

[0015] Based on the proportional data corresponding to each first sample screen, obtain the correction matrix corresponding to the target mode.

[0016] The brightness correction data is determined based on the correction matrix;

[0017] Preferably, the correction matrix is ​​divided into multiple matrix blocks according to preset division conditions, and the values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

[0018] Preferably, the multiple matrix blocks include 4 matrix blocks, and each matrix block is 2*2.

[0019] In one embodiment, before obtaining the brightness correction data corresponding to the target mode, the method further includes:

[0020] The third brightness feature data corresponding to the second sample screen at each mode position is obtained by the application device, and the fourth brightness feature data corresponding to each second sample screen is obtained by the experimental device.

[0021] Based on the third and fourth brightness characteristic data, determine whether the application equipment and experimental equipment are calibrated.

[0022] In one embodiment, determining whether the application device and the experimental device are calibrated based on each third luminance feature data and each fourth luminance feature data includes:

[0023] The application statistics data corresponding to the application devices are determined based on each third brightness characteristic data, and the experimental statistics data corresponding to the experimental devices are determined based on each fourth brightness characteristic data.

[0024] Based on the third and fourth brightness characteristic data, comprehensive statistical data are determined;

[0025] Based on application statistics, experimental statistics, and comprehensive statistics, determine whether the application equipment and experimental equipment are calibrated and aligned.

[0026] In one embodiment, determining whether the application device and the experimental device are calibrated based on application statistics, experimental statistics, and comprehensive statistics includes:

[0027] Calculate the statistical mean of application statistics and experimental statistics;

[0028] If the mean of the statistical data is less than or equal to the comprehensive statistical data, then the application equipment and experimental equipment are to be calibrated.

[0029] If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application equipment and the experimental equipment are not calibrated.

[0030] Secondly, this application also provides a data correction device, comprising:

[0031] The first acquisition module is used to acquire target brightness feature data corresponding to the target screen through the application device;

[0032] The second acquisition module is used to acquire the brightness correction data corresponding to the target module based on the target module corresponding to the target screen.

[0033] The correction module is used to correct the target brightness feature data based on the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0034] Thirdly, embodiments of this application provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect above.

[0036] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0037] The aforementioned data correction method, apparatus, device, readable storage medium, and program product can acquire target brightness feature data corresponding to the target screen through the application device, acquire brightness correction data corresponding to the target module based on the target screen, and correct the target brightness feature data based on the brightness correction data and the correction strategy corresponding to the experimental equipment. Thus, before correcting the target screen using the correction strategy corresponding to the experimental equipment, it is first determined whether the application device used in the actual application and the experimental equipment used to design the correction strategy are calibrated. If not, the brightness correction data corresponding to the target module is acquired, and the target brightness feature data is corrected by combining the brightness correction data and the correction strategy. This avoids the problem of low correction accuracy caused by the application device used in the actual application and the experimental equipment used in the experiment not being calibrated. The technical solution provided in this application improves the correction accuracy of the correction strategy. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a diagram illustrating the application environment of a data correction method in one embodiment;

[0040] Figure 2 This is a flowchart illustrating a data correction method in one embodiment;

[0041] Figure 3 This is a flowchart illustrating step 202 in another embodiment;

[0042] Figure 4 This is a flowchart illustrating the process of determining whether the application device and the experimental device are calibrated in another embodiment;

[0043] Figure 5 This is a flowchart illustrating the data correction method in another embodiment;

[0044] Figure 6 This is a structural block diagram of a data correction device in one embodiment;

[0045] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0047] During the manufacturing of monitor panels, uneven brightness may occur due to various reasons. Therefore, Demura technology was developed to correct the brightness data of the panel.

[0048] In related technologies, the Demura algorithm is usually designed by taking pictures of sample screens in the laboratory using laboratory cameras. Subsequently, in the production line, the brightness data of the screens produced on the production line is corrected based on the designed Demura algorithm and the cameras in the production line.

[0049] However, the laboratory camera used in designing the Demura algorithm may differ from the camera used in the actual production line. The brightness data of the screen collected by the different cameras will also differ. If the Demura algorithm designed with laboratory cameras is directly used to correct the brightness data of the screen produced on the production line, the accuracy of the correction will be reduced.

[0050] In view of this, this application provides a data correction method, apparatus, device, readable storage medium, and program product. Through an application device, target brightness feature data corresponding to a target screen can be obtained. Based on the target module corresponding to the target screen, brightness correction data corresponding to the target module can be obtained. Based on the brightness correction data and the correction strategy corresponding to the experimental equipment, the target brightness feature data can be corrected. Thus, before correcting the target screen using the correction strategy corresponding to the experimental equipment, it is first determined whether the application device used in the actual application and the experimental equipment used to design the correction strategy are calibrated. If not, the brightness correction data corresponding to the target module is obtained, and the target brightness feature data is corrected by combining the brightness correction data and the correction strategy. This avoids the problem of low correction accuracy caused by the application device not being calibrated with the experimental equipment used in the experiment. The technical solution provided by this application improves the correction accuracy of the correction strategy.

[0051] The data correction method provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is illustrated. The data storage system stores the data that server 101 needs to process. The data storage system can be integrated onto server 101, or it can be located on the cloud or other network servers. Server 101 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0052] In an exemplary embodiment, Figure 2 As shown, a data correction method is provided, which is applied to... Figure 1 Taking server 101 as an example, the explanation includes the following steps 201 to 203. Wherein:

[0053] Step 201: Obtain the target brightness feature data corresponding to the target screen through the application device.

[0054] In this embodiment of the application, the application device can be a device used in the production line that produces the target screen to collect target brightness feature data. The application device can be used to take a picture of the target screen. The target screen can be a display screen that needs to be corrected for brightness feature data. The target brightness feature data can be used to characterize the brightness features of different pixels of the target screen.

[0055] In one possible implementation, the application device communicates with the server. After the application device collects the target brightness feature data corresponding to the target screen, the server can optionally directly receive the target brightness feature data sent by the application device; alternatively, the server can send a collection command to the application device to obtain the target brightness feature data sent by the application device in response to the collection command.

[0056] Step 202: Obtain the brightness correction data corresponding to the target module based on the target module corresponding to the target screen.

[0057] In the embodiments of this application, the experimental equipment may be a device used to collect data when designing the correction strategy (related Demura algorithm), such as a camera.

[0058] It is understandable that there may be some differences between experimental equipment and application equipment. Before correcting the target brightness feature data, the server can check whether the application equipment and experimental equipment are calibrated to avoid the problem of low correction accuracy due to equipment differences.

[0059] In one possible implementation, the server can obtain the device parameters of the application device and the experimental device respectively. The device parameters may include focal length, measurement accuracy, etc. The server can compare the differences between the device parameters of the application device and the device parameters of the experimental device to determine whether the application device and the experimental device are calibrated.

[0060] In another possible implementation, the server can collect feature data of the sample screen through experimental equipment, and then collect feature data of the sample screen through application equipment. The server can compare the differences between the feature data of the sample screen collected by the experimental equipment and the feature data of the sample screen collected by the application equipment to determine whether the application equipment and the experimental equipment are calibrated.

[0061] Optionally, when the application device and the experimental device are calibrated together, the server can directly use the correction strategy corresponding to the experimental device to correct the target brightness feature data.

[0062] Optionally, in the absence of calibration between the application device and the experimental device, in order to avoid the problem of low correction accuracy due to device differences, the server can obtain the brightness correction data corresponding to the target module based on the target module corresponding to the target screen, and in subsequent steps, combine the brightness correction data with the correction strategy corresponding to the experimental device to correct the target brightness feature data.

[0063] In the embodiments of this application, the target module can be the position of the target screen body on the screen panel. The screen panel is a large piece of material used to manufacture the display screen. A screen panel can be cut into multiple screen bodies. Different positions on the screen panel are called modules, such as the center, upper edge, lower edge, upper left corner, upper right corner, etc.

[0064] Brightness correction data can be used to compensate for the differences in data acquisition between the application device and the experimental device. After the server corrects the target brightness feature data collected by the application device using brightness correction data, the corrected target brightness feature data eliminates the device differences.

[0065] It is understandable that the screens of different modules on the screen panel may differ. Therefore, different modules correspond to different brightness correction data. Optionally, there is a mapping relationship between each module and the brightness correction data, and the server can directly obtain the brightness correction data corresponding to the target module.

[0066] Optionally, the server can collect brightness feature data of multiple sample screens of the target module through application devices and experimental equipment. The server can then calculate the brightness correction data corresponding to the target module based on the collected data.

[0067] Step 203: Correct the target brightness feature data according to the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0068] Optionally, the server can obtain the correction strategy input by the user through an external input device; alternatively, the server can directly obtain the correction strategy corresponding to the experimental device from the database.

[0069] In one possible implementation, the server can use the brightness correction data and the target brightness feature data as input parameters for the correction strategy, and execute the correction strategy to obtain the corrected target brightness feature data.

[0070] In another possible implementation, the server can use the brightness correction data to perform a first correction process on the target brightness feature data to obtain first brightness correction data, and then use a correction strategy to perform a second correction process on the first brightness correction data to obtain second brightness correction data. The server can use the second brightness correction data as the result of the correction process. In this embodiment, the first brightness correction data is brightness feature data that has eliminated device differences. The server uses the correction strategy to perform a second correction process on the first brightness correction data, which can achieve the correction effect of the correction strategy and improve the correction accuracy.

[0071] In the above embodiments, before using the correction strategy corresponding to the experimental equipment to correct the target screen, it is first determined whether the application equipment used in the actual application and the experimental equipment used to design the correction strategy are calibrated. If not, the brightness correction data corresponding to the target module is obtained, and the target brightness feature data is corrected by combining the brightness correction data and the correction strategy. This avoids the problem of low correction accuracy of the correction strategy caused by the application equipment used in the actual application and the experimental equipment used in the experiment not being calibrated. The technical solution provided by this application improves the correction accuracy of the correction strategy.

[0072] In one embodiment, based on the above Figure 2 The illustrated embodiment can be found in [reference]. Figure 3 This embodiment relates to the process of acquiring brightness correction data corresponding to the target module. For example... Figure 3 As shown, step 202 may include steps 301 and 302.

[0073] Step 301: Obtain first brightness feature data corresponding to multiple first sample screens under the target module position through the application device, and obtain second brightness feature data corresponding to multiple first sample screens under the target module position through the experimental device.

[0074] For a target module, the server can acquire first brightness feature data corresponding to multiple first sample screens under the target module through the application device, and acquire second brightness feature data corresponding to multiple first sample screens under the target module through the experimental device. Optionally, after the application device and the experimental device acquire the first brightness feature data and the second brightness feature data respectively, the server can obtain the first brightness feature data and the second brightness feature data sent by the application device and the experimental device respectively through the communication protocol. Optionally, the server can send acquisition commands to the application device and the experimental device respectively, thereby obtaining the first brightness feature data and the second brightness feature data returned by the application device and the experimental device in response to the acquisition commands.

[0075] Step 302: Obtain brightness correction data based on each first brightness feature data and each second brightness feature data.

[0076] In one possible implementation, the server can calculate the brightness correction data corresponding to the target mode based on the difference between each first brightness feature data and each second brightness feature data.

[0077] In another possible implementation, for each first sample screen, the server can calculate the ratio of the second brightness feature data to the first brightness feature data. Based on the ratio data corresponding to each first sample screen, the server can obtain the correction matrix corresponding to the target mode. Based on the correction matrix, the server can determine the brightness correction data.

[0078] In this embodiment, the target module corresponds to at least three first sample screens. For each first sample screen, the ratio of the second brightness feature data to the first brightness feature data, i.e., the ratio, can be calculated. The specific calculation process can be found in Table 1.

[0079]

[0080] Table 1

[0081] Among them, CSV1 and CSV0 are the first brightness feature data and the second brightness feature data corresponding to one first sample screen, and CSV1* and CSV0* are the first brightness feature data and the second brightness feature data corresponding to another first sample screen.

[0082] After obtaining the proportional data corresponding to multiple first sample screens under the target mode, the server can calculate the mean data corresponding to each proportional data. Taking the two first sample screens in Table 1 as an example, the mean data can be found in Table 2:

[0083]

[0084] Table 2

[0085] In this embodiment of the application, the server can use the mean data as the correction matrix corresponding to the target modulus. Optionally, the server can directly use the correction matrix as the brightness correction data.

[0086] Optionally, it is understood that the amount of data contained in the correction matrix is ​​very large. In order to facilitate calculation, the correction matrix can be simplified to obtain the final brightness correction data.

[0087] In this embodiment of the application, regarding the simplified processing, the server can divide the correction matrix into multiple matrix blocks according to preset partitioning conditions, and perform averaging on the elements in each matrix block so that each matrix block becomes a numerical element, and each numerical element constitutes the final brightness correction data.

[0088] For example, the server can divide the mean matrix in Table 2 into four 2×2 matrix blocks, and then perform mean processing on the elements in each matrix block to obtain the final brightness correction data, which can be a matrix. .

[0089] In one embodiment, based on the above Figure 2 The illustrated embodiment can be found in [reference]. Figure 4 This embodiment relates to the process of determining whether the application device and the experimental device are calibrated before acquiring the brightness correction data corresponding to the target module. For example... Figure 4 As shown, the process may include steps 401 and 402.

[0090] Step 401: Obtain the third brightness feature data corresponding to the second sample screen at each module position through the application device, and obtain the fourth brightness feature data corresponding to each second sample screen through the experimental device.

[0091] In order to accurately detect whether the application equipment and the experimental equipment are calibrated, the server can collect brightness feature data of the second sample screen under multiple modes through the application equipment and the experimental equipment respectively, so as to obtain the third brightness feature data and the fourth brightness feature data corresponding to the second sample screen.

[0092] Optionally, after the application device and the experimental device respectively collect the third luminance feature data and the fourth luminance feature data, the server can obtain the third luminance feature data and the fourth luminance feature data sent by the application device and the experimental device respectively through the communication protocol; alternatively, the server can send acquisition commands to the application device and the experimental device respectively, thereby obtaining the third luminance feature data and the fourth luminance feature data returned by the application device and the experimental device in response to the acquisition commands.

[0093] Step 402: Based on the third and fourth brightness characteristic data, determine whether the application equipment and the experimental equipment are calibrated.

[0094] In one possible implementation, for each second sample screen, the server can calculate the difference between its corresponding third brightness feature data and fourth brightness feature data, and comprehensively determine whether the difference between the third brightness feature data and fourth brightness feature data corresponding to each second sample screen is greater than a preset difference range. If it is greater, the server determines that the application device and the experimental device are not calibrated. If it is not greater, the server determines that the application device and the experimental device are calibrated.

[0095] In another possible implementation, the server can determine the application statistics corresponding to the application device based on each third brightness feature data, and determine the experimental statistics corresponding to the experimental device based on each fourth brightness feature data. The server can also determine the comprehensive statistics based on each third brightness feature data and each fourth brightness feature data. In this way, the server can determine whether the application device and the experimental device are calibrated based on the application statistics, experimental statistics, and comprehensive statistics.

[0096] For each module with multiple second sample screens, its corresponding third brightness feature data can include brightness feature data acquired twice. The server can then calculate the difference between the two brightness feature data points included in the third brightness feature data; this difference is the application difference corresponding to the application device. The server can calculate the application standard deviation of each application difference and the mean of the application standard deviations to obtain the application statistics data corresponding to the application device. The calculation process for experimental statistics data is the same as that for application statistics data; that is, the fourth brightness feature data can also include brightness feature data acquired twice. It is understandable that the differences between the third and fourth brightness feature data can be determined based on the application statistics data and experimental statistics data, thereby determining whether the application device and experimental device are calibrated accordingly.

[0097] For example, referring to Table 3, the third brightness feature data includes a brightness feature data CSV1, where each element in CSV1 represents the brightness feature data of each pixel of the second sample screen:

[0098]

[0099] Table 3

[0100] Referring to Table 4, another luminance feature data CSV1* is included in the third luminance feature data:

[0101]

[0102] Table 4

[0103] To calculate the difference between CSV1 and CSV1*, please refer to Table 5:

[0104]

[0105] Table 5

[0106] Based on this difference, the server can calculate the application standard deviation σ(1) corresponding to the second sample screen as 0.00846. Based on the above process, the server can calculate the application standard deviation corresponding to each second sample screen, calculate the mean of each application standard deviation, and the server can use the mean of each application standard deviation as the application statistics data corresponding to the application device.

[0107] Similarly, referring to Table 6, CSV0 and CSV0* are the brightness feature data included in the fourth brightness feature data. The calculation process of the experimental statistical data can be found in Table 6:

[0108]

[0109] Table 6

[0110] The server can calculate the experimental standard deviation σ(0) corresponding to the second sample screen as 0.170002. The server can calculate the experimental standard deviation corresponding to each second sample screen and calculate the mean of each experimental standard deviation. The server can use the mean of each experimental standard deviation as the experimental statistical data corresponding to the application equipment.

[0111] For the calculation process of the second application statistics for each second sample screen, the server can calculate the ratio between a brightness feature data CSV1 included in the third brightness feature data and a brightness feature data CSV0 included in the fourth brightness feature data, and calculate the first standard deviation of the ratio σ(0-1). Similarly, the server can calculate the second standard deviation of the ratio σ(0*-1*) based on the ratio between another brightness feature data CSV1* included in the third brightness feature data and a brightness feature data CSV0* included in the fourth brightness feature data. The server can calculate the mean AVG_σ(0-1) between the first standard deviation of the ratio and the second standard deviation of the ratio σ(0*-1*) as the sub-comprehensive statistics for the second sample screen, and the server can calculate the comprehensive statistics for each sub-comprehensive statistics.

[0112] For the sub-synthetic statistics of the second sample screen, please refer to Table 7:

[0113]

[0114] Table 7

[0115] After obtaining statistical data, experimental statistical data, and comprehensive statistical data, the server can calculate the mean of the statistical data of the application statistical data and the experimental statistical data, and detect whether the mean of the statistical data is greater than the comprehensive statistical data. This detection process can be expressed as: σ(0-1)≤[σ(0)+σ(1)] / 2, where σ(0-1) represents the ratio standard deviation, σ(0) represents the experimental standard deviation σ(1), and σ(1) represents the application standard deviation.

[0116] Optionally, if the average statistical data is less than or equal to the comprehensive statistical data, it is determined that the application equipment and the experimental equipment are calibrated. Alternatively, if the average statistical data is greater than the comprehensive statistical data, it is determined that the application equipment and the experimental equipment are not calibrated.

[0117] In one embodiment, refer to Figure 5 An exemplary data correction method is provided, which can be applied to Figure 1 The server in the implementation environment shown.

[0118] Step 501: Obtain the target brightness feature data corresponding to the target screen through the application device.

[0119] Step 502: Obtain the third brightness feature data corresponding to the second sample screen at each module position through the application device, and obtain the fourth brightness feature data corresponding to each second sample screen through the experimental device.

[0120] Step 503: Determine the application statistics data corresponding to the application device based on each third brightness feature data, and determine the experimental statistics data corresponding to the experimental device based on each fourth brightness feature data.

[0121] Step 504: Determine the comprehensive statistical data based on the third luminance feature data and the fourth luminance feature data.

[0122] Step 505: Calculate the mean of the statistical data of the application statistics and the experimental statistics.

[0123] Step 506: If the average statistical data is less than or equal to the comprehensive statistical data, then the application equipment and experimental equipment are calibrated.

[0124] Step 507: If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application equipment and the experimental equipment are not calibrated.

[0125] Step 508: Obtain the target module corresponding to the target screen.

[0126] Step 509: Obtain first brightness feature data corresponding to multiple first sample screens under the target module position through the application device, and obtain second brightness feature data corresponding to multiple first sample screens under the target module position through the experimental device.

[0127] Step 510: For each first sample screen, calculate the ratio of the second brightness feature data to the first brightness feature data.

[0128] Step 511: Obtain the correction matrix corresponding to the target mode position based on the proportional data corresponding to each first sample screen.

[0129] Step 512: Determine the brightness correction data based on the correction matrix.

[0130] Step 513: Correct the target brightness feature data according to the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0131] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0132] Based on the same inventive concept, this application also provides a data correction apparatus for implementing the data correction method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more data correction apparatus embodiments provided below can be found in the limitations of the data correction method described above, and will not be repeated here.

[0133] In an exemplary embodiment, Figure 6 As shown, a data correction device is provided, comprising: a first acquisition module 601, a second acquisition module 602, and a correction module 603, wherein:

[0134] The first acquisition module 601 is used to acquire target brightness feature data corresponding to the target screen through the application device;

[0135] The second acquisition module 602 is used to acquire the brightness correction data corresponding to the target module based on the target module corresponding to the target screen.

[0136] The correction module 603 is used to correct the target brightness feature data according to the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0137] In one embodiment, the second acquisition module 602 includes:

[0138] The sample feature data acquisition unit is used to acquire first brightness feature data corresponding to multiple first sample screens under the target module through the application device, and to acquire second brightness feature data corresponding to each first sample screen through the experimental device.

[0139] The data acquisition unit is configured to acquire the brightness correction data based on each of the first brightness feature data and each of the second brightness feature data.

[0140] In one embodiment, the data acquisition unit is specifically used to perform:

[0141] For each of the first sample screens, calculate the ratio of the second brightness feature data to the first brightness feature data;

[0142] Based on the proportional data corresponding to each of the first sample screens, obtain the correction matrix corresponding to the target module.

[0143] The brightness correction data is determined based on the correction matrix;

[0144] Preferably, the correction matrix is ​​divided into multiple matrix blocks according to preset division conditions, and the values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

[0145] Preferably, the plurality of matrix blocks includes four matrix blocks, and each matrix block is 2*2.

[0146] In one embodiment, the device further includes:

[0147] The sample feature data acquisition module is used to acquire the third brightness feature data corresponding to the second sample screen at each module position through the application device, and to acquire the fourth brightness feature data corresponding to each second sample screen through the experimental device.

[0148] The calibration module is used to determine whether the application device and the experimental device are calibrated based on the third brightness feature data and the fourth brightness feature data.

[0149] In one embodiment, the benchmarking module includes:

[0150] The first statistical unit is used to determine the application statistics data corresponding to the application device based on each of the third brightness feature data, and to determine the experimental statistics data corresponding to the experimental device based on each of the fourth brightness feature data.

[0151] The second statistical unit is used to determine comprehensive statistical data based on each of the third brightness feature data and each of the fourth brightness feature data;

[0152] The calibration unit is used to determine whether the application equipment and the experimental equipment are calibrated based on the application statistics, the experimental statistics, and the comprehensive statistics.

[0153] In one embodiment, the calibration unit is specifically used to perform:

[0154] Calculate the statistical mean of the application statistics and the experimental statistics;

[0155] If the average of the statistical data is less than or equal to the comprehensive statistical data, then it is determined that the application equipment and the experimental equipment are calibrated.

[0156] If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application device and the experimental device are not calibrated.

[0157] Each module in the aforementioned data correction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0158] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data correction data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a data correction method.

[0159] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0160] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0161] The target brightness feature data corresponding to the target screen is obtained through the application device;

[0162] Based on the target module corresponding to the target screen, obtain the brightness correction data corresponding to the target module;

[0163] The target brightness feature data is corrected based on the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0164] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0165] The application device is used to obtain first brightness feature data corresponding to multiple first sample screens under the target module, and the experimental device is used to obtain second brightness feature data corresponding to each first sample screen.

[0166] The brightness correction data is obtained based on each of the first brightness feature data and each of the second brightness feature data.

[0167] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0168] For each of the first sample screens, calculate the ratio of the second brightness feature data to the first brightness feature data;

[0169] Based on the proportional data corresponding to each of the first sample screens, obtain the correction matrix corresponding to the target module.

[0170] The brightness correction data is determined based on the correction matrix;

[0171] Preferably, the correction matrix is ​​divided into multiple matrix blocks according to preset division conditions, and the values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

[0172] Preferably, the plurality of matrix blocks includes four matrix blocks, and each matrix block is 2*2.

[0173] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0174] The third brightness feature data corresponding to the second sample screen under each module position is obtained by the application device, and the fourth brightness feature data corresponding to each second sample screen is obtained by the experimental device.

[0175] Based on the third brightness characteristic data and the fourth brightness characteristic data, determine whether the application device and the experimental device are calibrated.

[0176] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0177] The application statistics data corresponding to the application device are determined based on each of the third brightness feature data, and the experimental statistics data corresponding to the experimental device are determined based on each of the fourth brightness feature data.

[0178] Based on the third brightness characteristic data and the fourth brightness characteristic data, a comprehensive statistical data set is determined;

[0179] Based on the application statistics, the experimental statistics, and the comprehensive statistics, determine whether the application equipment and the experimental equipment are calibrated.

[0180] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0181] Calculate the statistical mean of the application statistics and the experimental statistics;

[0182] If the average of the statistical data is less than or equal to the comprehensive statistical data, then it is determined that the application equipment and the experimental equipment are calibrated.

[0183] If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application device and the experimental device are not calibrated.

[0184] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0185] The target brightness feature data corresponding to the target screen is obtained through the application device;

[0186] Based on the target module corresponding to the target screen, obtain the brightness correction data corresponding to the target module;

[0187] The target brightness feature data is corrected based on the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0188] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0189] The application device is used to obtain first brightness feature data corresponding to multiple first sample screens under the target module, and the experimental device is used to obtain second brightness feature data corresponding to each first sample screen.

[0190] The brightness correction data is obtained based on each of the first brightness feature data and each of the second brightness feature data.

[0191] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0192] For each of the first sample screens, calculate the ratio of the second brightness feature data to the first brightness feature data;

[0193] Based on the proportional data corresponding to each of the first sample screens, obtain the correction matrix corresponding to the target module.

[0194] The brightness correction data is determined based on the correction matrix;

[0195] Preferably, the correction matrix is ​​divided into multiple matrix blocks according to preset division conditions, and the values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

[0196] Preferably, the plurality of matrix blocks includes four matrix blocks, and each matrix block is 2*2.

[0197] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0198] The third brightness feature data corresponding to the second sample screen under each module position is obtained by the application device, and the fourth brightness feature data corresponding to each second sample screen is obtained by the experimental device.

[0199] Based on the third brightness characteristic data and the fourth brightness characteristic data, determine whether the application device and the experimental device are calibrated.

[0200] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0201] The application statistics data corresponding to the application device are determined based on each of the third brightness feature data, and the experimental statistics data corresponding to the experimental device are determined based on each of the fourth brightness feature data.

[0202] Based on the third brightness characteristic data and the fourth brightness characteristic data, a comprehensive statistical data set is determined;

[0203] Based on the application statistics, the experimental statistics, and the comprehensive statistics, determine whether the application equipment and the experimental equipment are calibrated.

[0204] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0205] Calculate the statistical mean of the application statistics and the experimental statistics;

[0206] If the average of the statistical data is less than or equal to the comprehensive statistical data, then it is determined that the application equipment and the experimental equipment are calibrated.

[0207] If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application device and the experimental device are not calibrated.

[0208] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0209] The target brightness feature data corresponding to the target screen is obtained through the application device;

[0210] Based on the target module corresponding to the target screen, obtain the brightness correction data corresponding to the target module;

[0211] The target brightness feature data is corrected based on the brightness correction data and the correction strategy corresponding to the experimental equipment.

[0212] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0213] The application device is used to obtain first brightness feature data corresponding to multiple first sample screens under the target module, and the experimental device is used to obtain second brightness feature data corresponding to each first sample screen.

[0214] The brightness correction data is obtained based on each of the first brightness feature data and each of the second brightness feature data.

[0215] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0216] For each of the first sample screens, calculate the ratio of the second brightness feature data to the first brightness feature data;

[0217] Based on the proportional data corresponding to each of the first sample screens, obtain the correction matrix corresponding to the target module.

[0218] The brightness correction data is determined based on the correction matrix;

[0219] Preferably, the correction matrix is ​​divided into multiple matrix blocks according to preset division conditions, and the values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

[0220] Preferably, the plurality of matrix blocks includes four matrix blocks, and each matrix block is 2*2.

[0221] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0222] The third brightness feature data corresponding to the second sample screen under each module position is obtained by the application device, and the fourth brightness feature data corresponding to each second sample screen is obtained by the experimental device.

[0223] Based on the third brightness characteristic data and the fourth brightness characteristic data, determine whether the application device and the experimental device are calibrated.

[0224] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0225] The application statistics data corresponding to the application device are determined based on each of the third brightness feature data, and the experimental statistics data corresponding to the experimental device are determined based on each of the fourth brightness feature data.

[0226] Based on the third brightness characteristic data and the fourth brightness characteristic data, a comprehensive statistical data set is determined;

[0227] Based on the application statistics, the experimental statistics, and the comprehensive statistics, determine whether the application equipment and the experimental equipment are calibrated.

[0228] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0229] Calculate the statistical mean of the application statistics and the experimental statistics;

[0230] If the average of the statistical data is less than or equal to the comprehensive statistical data, then it is determined that the application equipment and the experimental equipment are calibrated.

[0231] If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application device and the experimental device are not calibrated.

[0232] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0233] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0234] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0235] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A data correction method, characterized in that, The method includes: The target brightness feature data corresponding to the target screen is obtained through the application device; The third brightness feature data corresponding to the second sample screen at each module position is obtained through the application device, and the fourth brightness feature data corresponding to each second sample screen is obtained through the experimental device; wherein, the application device is the device used by the production line that produces the target screen to collect the target brightness feature data, and the experimental device is the device used to collect data when designing the correction strategy; Based on the third brightness characteristic data and the fourth brightness characteristic data, determine whether the application device and the experimental device are calibrated. When the application device and the experimental device are calibrated together, the target brightness feature data is corrected using the correction strategy corresponding to the experimental device. When the application device and the experimental device are not calibrated together, the application device acquires first brightness feature data corresponding to multiple first sample screens under the target module position, and the experimental device acquires second brightness feature data corresponding to multiple first sample screens under the target module position. Based on each first brightness feature data and each second brightness feature data, brightness correction data corresponding to the target module position is obtained. Based on the brightness correction data and the correction strategy corresponding to the experimental device, the target brightness feature data is corrected. The target module position is the orientation of the target screen on the screen panel, the screen panel includes multiple screens, and different positions on the screen panel are module positions.

2. The method according to claim 1, characterized in that, The step of obtaining the brightness correction data based on each of the first brightness feature data and each of the second brightness feature data includes: For each of the first sample screens, calculate the ratio of the second brightness feature data to the first brightness feature data; Based on the proportional data corresponding to each of the first sample screens, obtain the correction matrix corresponding to the target module. The brightness correction data is determined based on the correction matrix.

3. The method according to claim 1, characterized in that, The step of determining whether the application device and the experimental device are calibrated based on the third luminance feature data and the fourth luminance feature data includes: The application statistics data corresponding to the application device are determined based on each of the third brightness feature data, and the experimental statistics data corresponding to the experimental device are determined based on each of the fourth brightness feature data. Based on the third brightness characteristic data and the fourth brightness characteristic data, a comprehensive statistical data set is determined; Based on the application statistics, the experimental statistics, and the comprehensive statistics, determine whether the application equipment and the experimental equipment are calibrated.

4. The method according to claim 3, characterized in that, The step of determining whether the application device and the experimental device are calibrated based on the application statistics, the experimental statistics, and the comprehensive statistics includes: Calculate the statistical mean of the application statistics and the experimental statistics; If the average of the statistical data is less than or equal to the comprehensive statistical data, then it is determined that the application equipment and the experimental equipment are calibrated. If the average of the statistical data is greater than the comprehensive statistical data, it is determined that the application device and the experimental device are not calibrated.

5. The method according to claim 2, characterized in that, Determining the brightness correction data based on the correction matrix includes: The correction matrix is ​​divided into multiple matrix blocks according to preset division conditions. The values ​​in each matrix block are averaged to obtain the average value corresponding to each matrix block. The average value is then determined as the brightness correction data.

6. The method according to claim 5, characterized in that, The plurality of matrix blocks includes four matrix blocks, and each of the matrix blocks is 2*2.

7. A data correction device, characterized in that, The device includes: The first acquisition module is used to acquire target brightness feature data corresponding to the target screen through the application device; The sample feature data acquisition module is used to acquire the third brightness feature data corresponding to the second sample screen at each module position through the application device, and to acquire the fourth brightness feature data corresponding to each second sample screen through the experimental device; wherein, the application device is the device used by the production line that produces the target screen to collect the target brightness feature data, and the experimental device is the device used to collect data when designing the correction strategy. The calibration module is used to determine whether the application device and the experimental device are calibrated based on the third brightness feature data and the fourth brightness feature data. The correction module is used to correct the target brightness feature data using the correction strategy corresponding to the experimental equipment when the application device and the experimental equipment are calibrated together; when the application device and the experimental equipment are not calibrated together, the module obtains first brightness feature data corresponding to multiple first sample screens under the target module position through the application device, and obtains second brightness feature data corresponding to multiple first sample screens under the target module position through the experimental equipment; obtains brightness correction data corresponding to the target module position based on each first brightness feature data and each second brightness feature data; and corrects the target brightness feature data based on the brightness correction data and the correction strategy corresponding to the experimental equipment; wherein, the target module position is the position of the target screen on the screen panel, the screen panel includes multiple screens, and different positions on the screen panel are module positions.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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