CN116994510A - Method, device, equipment and readable storage medium for detecting afterimage of display panel - Google Patents
Method, device, equipment and readable storage medium for detecting afterimage of display panel Download PDFInfo
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Abstract
The application discloses an afterimage detection method, device and equipment of a display panel and a readable storage medium, and belongs to the technical field of display. The method comprises the following steps: acquiring an original gray-scale image of a display panel, wherein the original gray-scale image is an image obtained by inputting signals of preset gray scales to all pixel points of the display panel at a first moment; acquiring a test gray-scale image of a display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to a plurality of checkerboard areas after a first moment and inputting signals of preset gray scales to all pixel points of the display panel after lasting a preset time period; and carrying out gray level change analysis and edge matching analysis on the original gray level image and the test gray level image, and determining whether residual images of black and white checkerboard pictures exist in the test gray level image. The method can accurately detect the residual image of the display panel.
Description
Technical Field
The present application relates to the field of display technologies, and in particular, to a method, an apparatus, a device, and a readable storage medium for detecting an afterimage of a display panel.
Background
With the progress of society, display panel technology has been widely used in the electronic display industry, and the display panel technology can improve the quality of image and video display.
The problem of panel afterimage often occurs in the display panel due to the characteristics of the display panel and the limitations of the operation of the display panel. Currently, in the detection of the residual image of a panel, subjective evaluation is usually performed by visual inspection, and the residual image of the display panel cannot be accurately detected.
Disclosure of Invention
The application provides an afterimage detection method, device and equipment for a display panel and a readable storage medium, which can accurately detect the afterimage of the display panel. The technical scheme is as follows:
in a first aspect, there is provided a method for detecting an afterimage of a display panel, the method including: acquiring an original gray-scale image of a display panel, wherein the original gray-scale image is an image obtained by inputting signals of preset gray scales to all pixel points of the display panel at a first moment; acquiring a test gray-scale image of a display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to a plurality of checkerboard areas after a first moment and inputting signals of preset gray scales to all pixel points of the display panel after lasting a preset time period; and carrying out gray level change analysis and edge matching analysis on the original gray level image and the test gray level image, and determining whether residual images of black and white checkerboard pictures exist in the test gray level image.
In some possible implementations, the method further includes: carrying out gray level change analysis on the original gray level image and the test gray level image, and determining whether each checkerboard area in the test gray level image meets the condition of face residual image; performing edge matching analysis on the original gray level image and the test gray level image, and determining whether each checkerboard area in the test gray level image meets the condition of edge line residual image; if the first checkerboard area meets the surface residual image condition and meets the edge line residual image condition, determining that the surface residual image exists in the first checkerboard area; wherein the first tessellation region is any one of a plurality of tessellation regions; and if the first checkerboard area meets the edge line afterimage condition and does not meet the face afterimage condition, determining that the edge line afterimage exists in the first checkerboard area.
In some possible implementations, the method further includes: determining the gray scale variation of the first checkerboard area according to the difference value between the test gray scale value and the original gray scale value; the test gray scale value is the gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is the gray scale average value of the first checkerboard area in the original gray scale image; determining a surface residual image parameter according to the ratio of the gray level variation to the original gray level value; determining whether the surface residual image parameter is larger than a preset surface residual image threshold value; if the surface residual image parameter is larger than a preset surface residual image threshold value, determining that the first checkerboard area meets the surface residual image condition; and if the surface residual image parameter is smaller than or equal to the preset surface residual image threshold value, determining that the first checkerboard area does not meet the surface residual image condition.
In some possible implementations, the method further includes: if the first checkerboard area has the surface residual image, determining the surface residual image grade of the first checkerboard area according to the surface residual image parameter and the preset grade corresponding relation.
In some possible implementations, the method further includes: determining the surface residual image parameters according to the following formula:
wherein K is an afterimage coefficient, deltaL A(m,n) Is the gray level variation of the first checkerboard area, L A(m,n) And b is a color perception degree coefficient for the original gray scale value.
In some possible implementations, the method further includes: determining a structural similarity index of the first edge and the second edge according to the test gray scale value and the original gray scale value; the test gray scale value is the gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is the gray scale average value of the first checkerboard area in the original gray scale image; the first edge is the edge of a first checkerboard area in the original gray-scale image; the second edge is the edge of the first checkerboard area in the test gray-scale image; determining whether the structural similarity index is greater than a preset similarity threshold; if the structural similarity index is larger than a preset similarity threshold, determining that the first checkerboard area meets the edge line image retention condition; if the structural similarity index is smaller than or equal to a preset similarity threshold, determining that the first checkerboard area does not meet the edge line afterimage condition.
In some possible implementations, the method further includes: determining a brightness factor and a brightness covariance of the first checkerboard area according to the test gray-scale value and the original gray-scale value; determining a contrast factor of the first checkerboard region according to the test brightness standard deviation and the original brightness standard deviation; the test brightness standard deviation is the brightness standard deviation of a first checkerboard area in the test gray-scale image, and the original gray-scale value is the brightness standard deviation of the first checkerboard area in the original gray-scale image; determining a structural factor of the first checkerboard region according to the test brightness standard deviation, the original brightness standard deviation and the brightness covariance; and determining the structural similarity index according to the brightness factor, the contrast factor and the structural factor.
According to the afterimage detection method of the display panel, provided by the embodiment of the application, through acquiring the original gray-scale image and the test gray-scale image of the display panel, gray-scale variation analysis and edge matching analysis are carried out on the original gray-scale image and the test gray-scale image, and whether the afterimage of a black-white checkered picture exists in the test gray-scale image is determined. Firstly, the method can objectively determine whether the residual image appears on the display panel, so that the accuracy of the residual image detection of the display panel is improved. Secondly, the method can realize the afterimage detection of the display panel through a software program, expensive equipment and a specific detection environment are not required to be used for evaluating the afterimage, and therefore cost and resources are saved. And thirdly, the method can realize the afterimage detection of the display panel only through gray level change analysis and edge matching analysis, thereby simplifying algorithm complexity and saving data resource cost and calculation time cost.
In a second aspect, an afterimage detection apparatus of a display panel is provided, where the afterimage detection apparatus of the display panel includes an acquisition module and a determination module.
In a third aspect, a computer device is provided, where the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the computer program when executed by the processor implements the method for detecting an afterimage of a display panel described above.
In a fourth aspect, a computer readable storage medium is provided, where a computer program is stored, the computer program implementing the above-mentioned picture detection method when executed by a processor.
It will be appreciated that the advantages of the second, third and fourth aspects may be found in the relevant description of the first aspect, and are not repeated here.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for detecting an afterimage of a display panel according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a black and white checkerboard image according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an example of an afterimage screen of a display panel according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating an exemplary process for determining whether each checkerboard region in a test gray-scale image satisfies a face image retention condition according to an embodiment of the present application;
FIG. 5 is a flowchart illustrating an exemplary process for determining whether each checkerboard region in a test gray-scale image satisfies an edge line image retention condition according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an afterimage detection device of a display panel according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
It should be understood that references to "a plurality" in this disclosure refer to two or more. In the description of the present application, "/" means or, unless otherwise indicated, for example, A/B may represent A or B; "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, in order to facilitate the clear description of the technical solution of the present application, the words "first", "second", etc. are used to distinguish the same item or similar items having substantially the same function and function. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.
Before explaining the embodiment of the present application in detail, an application scenario of the embodiment of the present application is described.
With the progress of society, display panel technology has been widely used in the electronic display industry, and the display panel technology can improve the quality of image and video display.
The problem of panel afterimage often occurs in the display panel due to the characteristics of the display panel and the limitations of the operation of the display panel. The panel afterimage refers to an image aftereffect generated by a slow response speed of pixels when the display panel rapidly switches images or videos. Currently, the following method is generally used to detect the afterimage of the display panel:
A. and (3) carrying out visual observation, namely directly observing the residual image effect of the display panel image in the switching process by naked eyes to carry out subjective evaluation. However, the visual inspection method is affected by subjective factors and individual differences, and cannot accurately detect the afterimage of the display panel.
B. The afterimage is evaluated by measuring the response time of the display panel when switching images by a professional device. However, professional equipment is generally expensive equipment, and is high in requirements for detection environment at the time of afterimage detection of a display panel, and thus, high in cost.
C. The afterimage is detected by analyzing the differences between image sequences or pixels of the display panel by an image processing algorithm, which may be a differential image algorithm, a moving object detection algorithm, an optical flow algorithm, or the like. However, the image processing algorithm requires a large amount of image data and complicated calculation steps, increasing data resource costs and calculation time costs.
Therefore, the application provides an afterimage detection method of a display panel, which is used for determining whether an afterimage exists in the display panel by carrying out gray level change analysis and edge matching analysis on an original gray level image and a test gray level image. The method can accurately detect the residual image of the display panel and can save resources and cost.
The following explains in detail an afterimage detection method of a display panel provided in an embodiment of the present application. The execution body of the method provided by the embodiment of the application may be a computer device, a processor, or any device including a processor, and the execution body will be described below as an example of the computer device.
Embodiment one:
fig. 1 is a flowchart of a method for detecting an afterimage of a display panel according to an embodiment of the present application. Referring to fig. 1, the method includes the following steps.
S101: the method comprises the steps of obtaining an original gray-scale image of a display panel, wherein the original gray-scale image is obtained by inputting signals with preset gray scales to all pixel points of the display panel at a first moment.
The first time may be any time before the black and white checkerboard picture is illuminated. The preset gray level can be set according to the requirement, the value range of the preset gray level can be 0 to 255, for example, the preset gray level can be 127, 0, 255 or the like. It should be noted that, the original gray-scale image is obtained before the black-and-white checkered picture is lightened, at this time, the gray-scale value of the image obtained by inputting the preset gray-scale signal to all the pixel points of the display panel will not be suddenly changed, i.e. the gray-scale values of all the pixel points in the original gray-scale image are the same.
Optionally, a signal of a preset gray level is input to the display panel, the display panel can display an original gray level image, at this time, the original gray level image can be obtained by photographing with the industrial camera, and the obtained original gray level image is stored in the computer device.
S102: the method comprises the steps of obtaining a test gray-scale image of a display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to a plurality of checkerboard areas after a first moment, and inputting signals with preset gray scales to all pixel points of the display panel after a preset duration.
After the original gray-scale image is obtained, the picture of the display panel is switched from the original gray-scale picture to the black-and-white checkered picture, so that the black-and-white checkered picture is kept for a preset time. Optionally, the preset duration may be set according to the requirement, and may be 30 minutes, 60 minutes, or the like. And then, inputting signals with preset gray scales into all pixel points of the display panel to obtain a test gray scale image.
Optionally, after the black-and-white checkerboard frame is kept for a preset time, a signal with preset gray scale is input to the display panel, the display panel can display a test gray scale image, at the moment, the test gray scale image can be obtained by photographing through the industrial camera, and the obtained test gray scale image is stored in the computer equipment.
Taking a preset gray scale as 127 as an example, after the original gray scale picture is switched to a black-white checkered picture and kept for 30 minutes, signals with the gray scale value of 127 are input to all pixel points of the display panel, and a test gray scale image is obtained.
Alternatively, the size of the checkerboard area may be set according to the proportion of the display panel, and the area size of each checkerboard area is the same, that is, the number of pixels in each checkerboard area is the same. For example, fig. 2 is a schematic diagram of a black-and-white checkerboard, and as shown in fig. 2, the display panel includes M rows and N columns of checkerboard areas, and the M rows and N columns of checkerboard areas are controlled to be displayed at black-and-white intervals, so as to obtain the black-and-white checkerboard.
When the black-and-white checkered picture is switched to the test gray-scale picture, the response speed of the pixels is slow, so that the gray-scale values of the pixels in some checkered areas of the black-and-white checkered picture are suddenly changed, and the test gray-scale picture generates image residues. For example, fig. 3 is a schematic diagram of an example of an afterimage of a display panel, as shown in fig. 3, a signal with a preset gray level of 127 is input to a test gray level screen, and after the black-and-white checkerboard screen is switched to the test gray level screen, afterimages of the black-and-white checkerboard screen exist at edges of checkerboard areas a (2, 2) and a (4, 3) and adjacent edges of the checkerboard areas a (2, 2) and a (2, 4) in the test gray level screen.
S103: and carrying out gray level change analysis and edge matching analysis on the original gray level image and the test gray level image, and determining whether residual images of black and white checkerboard pictures exist in the test gray level image.
The gray level change analysis is to compare the gray level of the original gray level image with the gray level of the test gray level image, that is, the original gray level image and the test gray level image are input with the same preset gray level signal, when the black and white checkerboard picture is switched to the test gray level image, the gray level value of the pixels of some checkerboard areas of the black and white checkerboard picture is suddenly changed due to slower response speed of the pixels, so that the image residue is generated on the test gray level image, the gray level value of the test gray level image is changed, the gray level value of the test gray level image is different from the gray level value of the original gray level image, and whether the residual image exists can be determined by comparing the gray level values of the original gray level image and the test gray level image.
The edge matching analysis is to compare the edges of each checkerboard area in the original gray-scale image and the test gray-scale image respectively to determine whether an afterimage exists. Referring to fig. 3, when the black-and-white checkerboard frame is switched to the test gray-scale frame, the line afterimage phenomenon easily occurs at the edges of the adjacent black-and-white checkerboard frames in the black-and-white checkerboard frame, and whether the afterimage occurs in the display panel can be accurately detected through edge matching analysis.
According to the afterimage detection method of the display panel, provided by the embodiment of the application, the original gray-scale image of the display panel is obtained, the test gray-scale image of the display panel is obtained, gray-scale change analysis and edge matching analysis are carried out on the original gray-scale image and the test gray-scale image, and whether the afterimage of a black-white checkered picture exists in the test gray-scale image is determined. Firstly, the method can objectively determine whether the residual image appears on the display panel, so that the accuracy of the residual image detection of the display panel is improved. Secondly, the method can realize the afterimage detection of the display panel through a software program, expensive equipment and a specific detection environment are not required to be used for evaluating the afterimage, and therefore cost and resources are saved. And thirdly, the method can realize the afterimage detection of the display panel only through gray level change analysis and edge matching analysis, thereby simplifying algorithm complexity and saving data resource cost and calculation time cost.
Embodiment two:
the gray level change analysis and the edge matching analysis provided by the embodiment of the application are explained in detail below.
In one embodiment, step S103 is described above: gray level change analysis and edge matching analysis are carried out on the original gray level image and the test gray level image, and whether residual images of black and white checkerboard pictures exist in the test gray level image is determined, which comprises the following steps:
A. and carrying out gray level change analysis on the original gray level image and the test gray level image, and determining whether each checkerboard area in the test gray level image meets the condition of the face residual image.
That is, the gray level variation analysis is to analyze the gray level variation of the original gray level image and the gray level image, and determine whether the gray level variation of each checkerboard area in the test gray level image meets the preset condition of the surface residual image.
The satisfaction of the surface image retention condition indicates that the surface image retention phenomenon possibly exists, and the non-satisfaction of the surface image retention condition indicates that the surface image retention phenomenon does not exist. Referring to fig. 3, when the residual image is a black-and-white checkerboard image switched to a test gray-scale image, the black-and-white checkerboard image has a residual in the test gray-scale image, the surface residual image is a residual of the black-and-white checkerboard image in the checkerboard region in the black-and-white checkerboard image corresponding to the test gray-scale image, and a residual of the black-and-white checkerboard image is present at the edge of the checkerboard region in the black-and-white checkerboard image corresponding to the test gray-scale image. The line afterimage is the residual of black and white checkered pictures at the edges of adjacent checkered areas in the corresponding black and white checkered pictures in the test gray-scale pictures.
B. And carrying out edge matching analysis on the original gray level image and the test gray level image, and determining whether each checkerboard area in the test gray level image meets the condition of edge line afterimage.
At this time, edge matching analysis is performed on the original gray-scale image and the test gray-scale image, and whether each corresponding checkerboard area in the test gray-scale image meets the condition of edge line afterimage is determined. The satisfaction of the line afterimage condition indicates that the display panel has the line afterimage, and the non-satisfaction of the line afterimage condition indicates that the display panel does not have the line afterimage.
C. And if the first checkerboard area meets the face residual image condition and meets the edge line residual image condition, determining that the face residual image exists in the first checkerboard area, wherein the first checkerboard area is any one of a plurality of checkerboard areas. And if the first checkerboard area meets the edge line afterimage condition and does not meet the face afterimage condition, determining that the edge line afterimage exists in the first checkerboard area.
The first checkerboard region is any one of black and white checkerboard images. That is, when any one of the checkerboard areas corresponding to the test gray-scale picture satisfies both the face-image-retention condition and the edge-line-image-retention condition, it is indicated that the face-image-retention exists in the checkerboard area. And if any corresponding checkerboard area in the test gray-scale picture only meets the edge line afterimage condition, indicating that the checkerboard area has the line afterimage.
The gray level change analysis and the edge matching analysis provided by the embodiment of the application determine whether each checkerboard region in the test gray level image meets the surface residual image condition and the line residual image condition, if the first checkerboard region meets the surface residual image condition and meets the edge line residual image condition, the first checkerboard region is determined to have the surface residual image, and if the first checkerboard region meets the edge line residual image condition and does not meet the surface residual image condition, the first checkerboard region is determined to have the edge line residual image. Firstly, the method not only can determine whether the afterimage exists, but also can determine whether the afterimage type is a surface afterimage or a line afterimage, and improves the practicality of afterimage detection of the display panel. And secondly, determining whether the surface residual image exists or not according to the judging result of the surface residual image condition and the line residual image condition, fully considering the characteristics of the surface residual image, and more accurately determining the surface residual image.
The following further explains the procedure of determining whether each checkerboard area in the test gray-scale image satisfies the face residual image condition according to the embodiment of the present application with reference to the drawings and the embodiments.
Embodiment III:
FIG. 4 is a flowchart illustrating an exemplary process for determining whether each checkerboard region in a test gray-scale image satisfies a face image retention condition according to an embodiment of the present application. Referring to fig. 4, taking the first tessellated region as an example, the method includes the steps of:
S201: determining the gray scale variation of the first checkerboard area according to the difference value between the test gray scale value and the original gray scale value; the test gray scale value is a gray scale average value of a first checkerboard area in the test gray scale image, and the original gray scale value is a gray scale average value of the first checkerboard area in the original gray scale image.
The first checkerboard area comprises a plurality of pixel points, each pixel point has a corresponding gray scale value, and the computer equipment can acquire the gray scale values of all the pixel points in the first checkerboard area, so that the gray scale average value of the first checkerboard area can be determined. Referring to fig. 2, for example, the first checkerboard area is a (1, 1), in which a includes 30 pixels, and a gray-scale average value of the first checkerboard area can be calculated according to the gray-scale value of each pixel.
Based on the gray scale average value of the first checkerboard area in the original gray scale image can be calculated to obtain an original gray scale value; the gray scale average value of the first checkerboard area in the test gray scale image can be calculated to obtain the test gray scale value. Thus, a difference between the test gray scale value and the original gray scale value can be calculated. For example, if the original gray-scale value is 127 and the test gray-scale value is 150, the difference between the test gray-scale value and the original gray-scale value can be calculated to be 23.
S202: and determining the parameters of the surface residual image according to the ratio of the gray level variation to the original gray level value.
The computer equipment can determine the gray level variation of the first checkerboard area according to the test gray level value and the original gray level value, and can determine the surface residual image parameter according to the gray level variation and the original gray level value. For example, the gray-scale variation is 23, the original gray-scale value is 127, and the face residual image parameter is calculated to be 0.181.
Alternatively, the surface residual image parameter may be calculated by equation (1) or a deformation of equation (1).
Wherein K is an afterimage coefficient, deltaL A(m,n) Is the gray level variation of the first checkerboard area, L A(m,n) And b is a color perception degree coefficient for the original gray scale value.
Alternatively, K and b may be set as desired. K is 1000, b is 2.2, deltaL A(m,n ) Is 23, L A(m,n ) For example, 127 may be calculated to obtain the face residual parameter S as 23.275.
S203: and determining whether the surface residual image parameter is larger than a preset surface residual image threshold value. If the surface image retention parameter is greater than the preset surface image retention threshold, S204 is executed, and if the surface image retention parameter is less than or equal to the preset surface image retention threshold, S205 is executed.
The face image retention threshold may be set as required, and may be, for example, 0.1.
S204: and determining that the first checkerboard area meets the face residual image condition.
For example, if the face residual image threshold is 0.1 and the face residual image parameter is 23.275, it is determined that the first checkerboard region satisfies the face residual image condition.
S205: and determining that the first checkerboard region does not meet the face residual condition.
In one implementation, when it is determined that the first checkerboard area has the surface residual image, the level of the surface residual image may be further determined according to the surface residual image parameter and the preset level correspondence. The grade of the face image is used to characterize the severity of the face image.
For example, the preset ranks may be A, B, C and D, where a ranks represent the highest degree of afterimage, B ranks represent the higher degree of afterimage, C ranks represent the medium degree of afterimage, and D ranks represent the lighter degree of afterimage. The surface image-following parameter interval corresponding to the A level is more than 10, the surface image-following parameter interval corresponding to the B level is more than 5 and less than or equal to 10, the surface image-following parameter interval corresponding to the C level is more than 1 and less than or equal to 5, and the surface image-following interval corresponding to the D level is more than 0.1 and less than or equal to 1. And determining the grade of the residual image according to the grade interval corresponding to the surface residual image parameter.
According to the method provided by the embodiment of the application, the gray scale variation of the first checkerboard area is determined according to the difference value between the test gray scale value and the original gray scale value, the surface afterimage parameter is determined according to the ratio of the gray scale variation to the original gray scale value, and when the surface afterimage parameter is larger than the preset surface afterimage threshold value, the condition of satisfying the surface afterimage is determined. By calculating the difference between the tested gray scale value and the original gray scale value, whether the gray scale value of the pixel of the first checkerboard in the display panel is suddenly changed can be specifically and quantitatively judged, so that the accuracy of the residual image detection of the display panel is improved. In addition, under the condition that the first checkerboard area has the surface residual image, the surface residual image grade can be further judged, so that a user can directly know the severity of the surface residual image, a reference standard is provided for subsequent maintenance of the display panel, and the practicability of residual image detection is improved.
Embodiment III:
the process of determining whether each checkerboard area in the test gray-scale image satisfies the condition of edge line afterimage according to the embodiment of the present application is further explained below with reference to the drawings and the embodiments.
FIG. 5 is a flowchart illustrating an exemplary process for determining whether each checkerboard region in a test gray-scale image satisfies an edge line image retention condition according to an embodiment of the present application. Referring to fig. 5, the method includes the steps of:
s301: determining a structural similarity index of the first edge and the second edge according to the test gray scale value and the original gray scale value; the test gray scale value is the gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is the gray scale average value of the first checkerboard area in the original gray scale image; the first edge is the edge of a first checkerboard area in the original gray-scale image; the second edge is the edge of the first checkerboard area in the test gray-scale image.
It will be appreciated that the positions of the first and second edges in the display panel are substantially identical. For example, referring to fig. 2, the first edge is the right edge of the checkerboard area a (1, 1) in the original grayscale image (i.e., the left edge of the checkerboard area a (1, 2)), and the second edge is the right edge of the checkerboard area a (1, 1) in the test grayscale image (i.e., the left edge of the checkerboard area a (1, 2).
In one embodiment, step S301 may be implemented by the following procedure:
A. and determining the brightness factor and the brightness covariance of the first checkerboard area according to the test gray-scale value and the original gray-scale value.
The luminance factor I can be calculated using equation (2).
Wherein mu x Is the gray level average value mu of the first checkerboard area in the original gray level image y To test the gray scale average value of the first checkerboard area in the gray scale image, C1 is a constant.
And determining the brightness covariance of the first checkerboard area according to the test gray level value and the original gray level value.
B. Determining a contrast factor of the first checkerboard region according to the test brightness standard deviation and the original brightness standard deviation; the test brightness standard deviation is the brightness standard deviation of the first checkerboard area in the test gray-scale image, and the original gray-scale value is the brightness standard deviation of the first checkerboard area in the original gray-scale image.
The contrast factor C can be calculated using equation (3).
Wherein sigma x Standard deviation of original brightness, sigma y To test the standard deviation of brightness, C2 is a constant.
C. And determining the structural factor of the first checkerboard region according to the test brightness standard deviation, the original brightness standard deviation and the brightness covariance.
The structural factor S can be calculated using equation (4).
Wherein sigma xy For luminance covariance, σ x Standard deviation of original brightness, sigma y To test the standard deviation of brightness, C3 is a constant.
D. And determining the structural similarity index according to the brightness factor, the contrast factor and the structural factor.
The structural similarity index M can be calculated using equation (5).
M＝I α C β S λ (5)
Wherein I is a brightness factor, C is a contrast factor, S is a structural factor, and alpha, beta and lambda are weight coefficients.
S302: determining whether the structural similarity index is greater than a preset similarity threshold, if the structural similarity index is greater than the preset similarity threshold, executing S303, and if the structural similarity index is less than or equal to the preset similarity threshold, executing S304.
It should be noted that, the structural similarity index calculated according to the above formula (5) has a value range greater than-1 and less than 1. If the structural similarity index is closer to 1, the first edge and the second edge are more similar, namely the original gray-scale image and the test gray-scale image are more similar; if the structural similarity index is closer to-1, the first edge and the second edge are more dissimilar, namely the original gray-scale image and the test gray-scale image are more dissimilar; if the structural similarity index is 0, the original gray-scale image and the test gray-scale image are similar.
The similarity threshold may be set manually according to the requirements, and may be 0.8, 0.7, 0.6, etc. For example, the similarity threshold is 0.8, the structural similarity index is 0.9, it may be determined that the first checkerboard region satisfies the edge line image retention condition, and if the calculated structural similarity index is greater than-1 and less than or equal to 0.8, it may be determined that the first checkerboard region does not satisfy the edge line image retention condition.
S303: and determining that the first checkerboard area meets the edge line afterimage condition.
S304: and determining that the first checkerboard area does not meet the edge line afterimage condition.
In this embodiment, a luminance factor and a luminance covariance of the first checkerboard area are determined according to the test gray-scale value and the original gray-scale value, a contrast factor of the first checkerboard area is determined according to the test luminance standard deviation and the original luminance standard deviation, a structural factor of the first checkerboard area is determined according to the test luminance standard deviation, the original luminance standard deviation and the luminance covariance, a structural similarity index is determined according to the luminance factor, the contrast factor and the structural factor, and when the structural similarity index is greater than a preset similarity threshold, it is determined that the first checkerboard area meets an edge line image retention condition. According to the method, the structural similarity index is obtained through calculation of the brightness factor, the contrast factor and the structural factor, and the similarity of the first edge and the second edge can be accurately determined, so that the residual image of the display panel can be accurately detected.
Fig. 6 is a schematic structural diagram of a frame detecting device according to the present application. The apparatus 600 includes:
the acquiring module 601 is configured to acquire an original grayscale image of the display panel, where the original grayscale image is an image obtained by inputting signals of a preset grayscale to all pixel points of the display panel at a first moment; the method comprises the steps of obtaining a test gray-scale image of a display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to a plurality of checkerboard areas after a first moment, and inputting signals of preset gray scales to all pixel points of the display panel after a preset duration;
the determining module 602 is configured to perform gray level change analysis and edge matching analysis on the original gray level image and the test gray level image, and determine whether an afterimage of the black and white checkerboard image exists in the test gray level image.
In some embodiments, the determining module 602 is further configured to perform gray level variation analysis on the original gray level image and the test gray level image, and determine whether each checkerboard area in the test gray level image meets the face residual image condition; performing edge matching analysis on the original gray level image and the test gray level image, and determining whether each checkerboard area in the test gray level image meets the condition of edge line residual image; if the first checkerboard area meets the surface residual image condition and meets the edge line residual image condition, determining that the surface residual image exists in the first checkerboard area; wherein the first tessellation region is any one of a plurality of tessellation regions; and if the first checkerboard area meets the edge line afterimage condition and does not meet the face afterimage condition, determining that the edge line afterimage exists in the first checkerboard area.
In some embodiments, the determining module 602 is further configured to determine a gray scale variation of the first checkerboard area according to a difference between the test gray scale value and the original gray scale value; the test gray scale value is the gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is the gray scale average value of the first checkerboard area in the original gray scale image; determining a surface residual image parameter according to the ratio of the gray level variation to the original gray level value; determining whether the surface residual image parameter is larger than a preset surface residual image threshold value; if the surface residual image parameter is larger than a preset surface residual image threshold value, determining that the first checkerboard area meets the surface residual image condition; and if the surface residual image parameter is smaller than or equal to the preset surface residual image threshold value, determining that the first checkerboard area does not meet the surface residual image condition.
In some embodiments, the determining module 602 is further configured to determine a level of the face residual image of the first checkerboard area according to the face residual image parameter and a preset level correspondence if the face residual image exists in the first checkerboard area.
In some embodiments, the determining module 602 is further configured to determine the surface image retention parameter according to the following formula:
wherein K is an afterimage coefficient, deltaL A(m,n) For the gray level variation of the first checkerboard area, L A(m,n) And b is a color perception degree coefficient for the original gray scale value.
In some embodiments, the determining module 602 is further configured to determine a structural similarity index of the first edge and the second edge according to the test gray scale value and the original gray scale value; the test gray scale value is the gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is the gray scale average value of the first checkerboard area in the original gray scale image; the first edge is the edge of a first checkerboard area in the original gray-scale image; the second edge is the edge of the first checkerboard area in the test gray-scale image; determining whether the structural similarity index is greater than a preset similarity threshold; if the structural similarity index is larger than a preset similarity threshold, determining that the first checkerboard area meets the edge line image retention condition; if the structural similarity index is smaller than or equal to a preset similarity threshold, determining that the first checkerboard area does not meet the edge line afterimage condition.
In some embodiments, the determining module 602 is further configured to determine a luminance factor and a luminance covariance of the first checkerboard area according to the test gray-scale value and the original gray-scale value; determining a contrast factor of the first checkerboard region according to the test brightness standard deviation and the original brightness standard deviation; the test brightness standard deviation is the brightness standard deviation of a first checkerboard area in the test gray-scale image, and the original gray-scale value is the brightness standard deviation of the first checkerboard area in the original gray-scale image; determining a structural factor of the first checkerboard region according to the test brightness standard deviation, the original brightness standard deviation and the brightness covariance; and determining the structural similarity index according to the brightness factor, the contrast factor and the structural factor.
The specific manner in which the apparatus 600 performs the afterimage detection method of the display panel and the resulting beneficial effects can be referred to the related description in the method embodiment, and will not be repeated here.
Fig. 7 is a schematic structural diagram of a computer device according to an embodiment of the present application. As shown in fig. 7, the computer device 700 includes: the steps in the method for detecting an afterimage of a display panel in the above embodiment are implemented by the processor 710, the memory 720, and the computer program 721 stored in the memory 720 and executable on the processor 710 when the processor 710 executes the computer program 721.
The computer device 700 may be a general purpose computer device or a special purpose computer device. In a specific implementation, the computer device 700 may be a desktop, a laptop, a network server, a palmtop, a mobile handset, a tablet, a wireless terminal device, a communication device, or an embedded device, and embodiments of the present application are not limited to the type of computer device 700. It will be appreciated by those skilled in the art that fig. 7 is merely an example of a computer device 700 and is not intended to limit the computer device 700, and may include more or fewer components than shown, or may combine certain components, or may include different components, such as input-output devices, network access devices, etc.
The processor 710 may be a central processing unit (Central Processing Unit, CPU), and the processor 710 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or may be any conventional processor.
Memory 720 may be an internal storage unit of computer device 700 in some embodiments, such as a hard disk or memory of computer device 700. The memory 720 may also be an external storage device of the computer device TH in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the computer device TH. Further, the memory 720 may also include both internal storage units and external storage devices of the computer device 700. The memory 720 is used to store an operating system, application programs, boot Loader (Boot Loader), data, and other programs, etc. The memory 720 may also be used to temporarily store data that has been output or is to be output.
Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the respective method embodiments described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the above-described method embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and where the computer program, when executed by a processor, may implement the steps of the above-described method embodiments. Wherein the computer program comprises computer program code which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal device, recording medium, computer Memory, ROM (Read-Only Memory), RAM (Random Access Memory ), CD-ROM (Compact Disc Read-Only Memory), magnetic tape, floppy disk, optical data storage device, and so forth. The computer readable storage medium mentioned in the present application may be a non-volatile storage medium, in other words, a non-transitory storage medium.
It should be understood that all or part of the steps to implement the above-described embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The computer instructions may be stored in the computer-readable storage medium described above.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided by the present application, it should be understood that the disclosed apparatus/computer device and method may be implemented in other manners. For example, the apparatus/computer device embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. An afterimage detection method of a display panel, wherein the display panel includes a plurality of checkerboard areas, the method comprising:
acquiring an original gray-scale image of the display panel, wherein the original gray-scale image is an image obtained by inputting signals with preset gray scales to all pixel points of the display panel at a first moment;
Acquiring a test gray-scale image of the display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to the plurality of checkerboard areas after the first time, and inputting signals of the preset gray scales to all pixel points of the display panel after the preset time length;
and carrying out gray level change analysis and edge matching analysis on the original gray level image and the test gray level image, and determining whether the residual image of the black-white checkerboard picture exists in the test gray level image.
2. The method of claim 1, wherein said performing gray scale variation analysis and edge matching analysis on said original gray scale image and said test gray scale image to determine whether there is an afterimage of said black and white checkerboard picture in said test gray scale image comprises:
gray level change analysis is carried out on the original gray level image and the test gray level image, and whether each checkerboard area in the test gray level image meets the condition of face residual image is determined;
performing edge matching analysis on the original gray-scale image and the test gray-scale image, and determining whether each checkerboard area in the test gray-scale image meets the condition of edge line afterimage;
If the first checkerboard area meets the surface residual image condition and meets the edge line residual image condition, determining that the first checkerboard area has the surface residual image; wherein the first tessellation region is any one of the plurality of tessellation regions;
and if the first checkerboard area meets the edge line afterimage condition and does not meet the surface afterimage condition, determining that an edge line afterimage exists in the first checkerboard area.
3. The method of claim 2, wherein said performing gray scale variation analysis on said original gray scale image and said test gray scale image to determine whether each of said checkerboard regions satisfies a face image retention condition comprises:
determining the gray scale variation of the first checkerboard area according to the difference value between the test gray scale value and the original gray scale value; the test gray scale value is a gray scale average value of the first checkerboard area in the test gray scale image, and the original gray scale value is a gray scale average value of the first checkerboard area in the original gray scale image;
determining a surface residual image parameter according to the ratio of the gray level variation to the original gray level value;
determining whether the surface residual image parameter is larger than a preset surface residual image threshold value;
If the surface residual image parameter is larger than a preset surface residual image threshold value, determining that the first checkerboard area meets the surface residual image condition;
and if the surface residual image parameter is smaller than or equal to a preset surface residual image threshold value, determining that the first checkerboard area does not meet the surface residual image condition.
4. A method according to claim 3, characterized in that the method further comprises:
and if the surface residual image exists in the first checkerboard area, determining the surface residual image grade of the first checkerboard area according to the surface residual image parameter and the preset grade corresponding relation.
5. The method of claim 3, wherein determining the face image retention parameter based on the ratio of the gray level variation to the original gray level value comprises:
determining the surface residual image parameters according to the following formula:
wherein K is an afterimage coefficient, deltaL A(m,n) For the gray level variation of the first checkerboard area, L A(m,n) And b is a color perception degree coefficient for the original gray scale value.
6. The method of claim 2, wherein performing edge matching analysis on the original grayscale image and the test grayscale image to determine whether each of the checkerboard areas in the test grayscale image satisfies an edge line afterimage condition comprises:
Determining a structural similarity index of the first edge and the second edge according to the test gray scale value and the original gray scale value; the test gray scale value is a gray scale average value of the first checkerboard area in the test gray scale image, the original gray scale value is a gray scale average value of the first checkerboard area in the original gray scale image, the first edge is an edge of the first checkerboard area in the original gray scale image, and the second edge is an edge of the first checkerboard area in the test gray scale image;
determining whether the structural similarity index is greater than a preset similarity threshold;
if the structural similarity index is larger than a preset similarity threshold, determining that the first checkerboard area meets the edge line afterimage condition;
and if the structural similarity index is smaller than or equal to a preset similarity threshold, determining that the first checkerboard area does not meet the edge line afterimage condition.
7. The method of claim 6, wherein determining a structural similarity index for the first edge and the second edge based on the test gray scale value and the original gray scale value comprises:
determining a brightness factor and a brightness covariance of the first checkerboard area according to the test gray-scale value and the original gray-scale value;
Determining a contrast factor of the first checkerboard region according to the test brightness standard deviation and the original brightness standard deviation; the test brightness standard deviation is the brightness standard deviation of the first checkerboard area in the test gray-scale image, and the original gray-scale value is the brightness standard deviation of the first checkerboard area in the original gray-scale image;
determining a structural factor of the first checkerboard region according to the test brightness standard deviation, the original brightness standard deviation and the brightness covariance;
and determining the structural similarity index according to the brightness factor, the contrast factor and the structural factor.
8. An afterimage detection device of a display panel, wherein the display panel includes a plurality of checkerboard areas, the afterimage detection device of the display panel includes:
an acquisition module for:
acquiring an original gray-scale image of the display panel, wherein the original gray-scale image is an image obtained by inputting signals with preset gray scales to all pixel points of the display panel at a first moment;
acquiring a test gray-scale image of the display panel, wherein the test gray-scale image is an image obtained by controlling the display panel to display black and white checkerboard pictures according to the plurality of checkerboard areas after the first time, and inputting signals of the preset gray scales to all pixel points of the display panel after the preset time length;
And the determining module is used for carrying out gray level change analysis and edge matching analysis on the original gray level image and the test gray level image and determining whether the residual image of the black-white checkerboard picture exists in the test gray level image.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, which computer program, when executed by the processor, implements the method according to any of claims 1 to 7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method according to any of claims 1 to 7.
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