CN117471730A - Method and device for detecting uneven brightness of display panel - Google Patents
Method and device for detecting uneven brightness of display panel Download PDFInfo
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Abstract
The application discloses a method and a device for detecting uneven brightness of a display panel. The brightness unevenness detecting method includes: extracting a plurality of test areas from the to-be-processed image of the panel to be tested, acquiring the brightness standard deviation of any two adjacent test areas based on the brightness value of each pixel in the test areas, acquiring the brightness non-uniformity judgment value of the panel to be tested based on the brightness difference value of each pixel and all the brightness standard deviations, and generating a result of the brightness non-uniformity of the type to be tested of the panel to be tested if the brightness non-uniformity judgment value is larger than the type threshold value corresponding to the type to be tested. According to the method and the device, automatic detection and classification can be carried out on uneven brightness of the display device, subjective influence can be avoided, detection results can be obtained rapidly, so that the time for demura processing in the production process is shortened, and the production efficiency is improved.
Description
Technical Field
The application relates to the technical field of display, in particular to a method and a device for detecting uneven brightness of a display panel.
Background
In the production process of the liquid crystal display panel (Liquid Crystal Display, LCD), the defects of uneven brightness, i.e. mura, of the picture are caused by factors such as array process. In order to eliminate mura to improve brightness uniformity of the panel, a demux process is generally used to compensate for brightness non-uniformity of the display panel.
When the demux process is performed during the production of the LCD panel, the type of the mura is first detected, and then brightness correction is performed by using a correction unit (block) of a corresponding size according to the type of the mura. Typically, the mura type is detected by using filters of different levels for the division. However, this approach has subjective limitations and affects production time.
Disclosure of Invention
The embodiment of the application provides a method and a device for detecting uneven brightness of a display panel, which are used for solving the technical problems that subjective limitation exists in the prior art and production time is influenced.
In order to solve the technical problems, the embodiment of the application discloses the following technical scheme:
in a first aspect, a method for detecting luminance unevenness of a display panel is provided, including:
acquiring brightness values of pixels in an image to be processed of a panel to be tested;
extracting a plurality of test areas from the image to be processed;
for each test area, acquiring a brightness difference value of each pixel based on a brightness value and a brightness target value of each pixel in the test area;
acquiring brightness standard deviations of any two adjacent test areas based on brightness values of all pixels in each test area aiming at any two adjacent test areas;
acquiring a brightness non-uniformity judgment value of the panel to be tested based on all brightness standard deviations and the brightness difference value of each pixel;
and generating a result of the brightness unevenness of the type to be detected of the panel to be detected under the condition that the brightness unevenness judging value is larger than a type threshold value corresponding to the type to be detected.
With reference to the first aspect, the type to be detected is a first type, and the size of the test area is m×n, which satisfies the following requirements: m=h, n=1, where H is the number of lines of the image to be processed;
extracting a plurality of test areas from the image to be processed, including:
and determining each column of pixels of the image to be processed as each test area, wherein the number of the test areas is W, and W is the number of columns of the image to be processed.
With reference to the first aspect, the type to be detected is a second type, and the size of the test area is m×n, which satisfies the following requirements: m=n, and m < min { H, W }; or the type to be detected is a third type, and the size of the test area is m×n, so that the following conditions are satisfied: m is not equal to n, and the smaller of m and n is smaller than min { H, W }; wherein H is the number of rows of the image to be processed, and W is the number of columns of the image to be processed;
extracting a plurality of test areas from the image to be processed, including:
and sequentially extracting each test area from the image to be processed by taking one column or one row as a step length until all pixels in the image to be processed are acquired, wherein the number of the plurality of test areas is (W-m) x (H-n).
With reference to the first aspect, the obtaining, for each of the test areas, a luminance difference value of each pixel based on a luminance value and a luminance target value of each pixel in the test area includes:
performing curve fitting on brightness values of all pixels in the test area aiming at each test area to obtain brightness fitting values corresponding to all pixels in the test area, wherein the brightness fitting values are the brightness target values of the pixels;
and acquiring the brightness difference value of each pixel based on the brightness value of each pixel and the corresponding brightness fitting value.
In combination with the first aspect, performing curve fitting on brightness values of all pixels in the test area to obtain brightness fitting values corresponding to all pixels in the test area, where the curve fitting comprises:
arranging all pixels in the test area according to the positions;
polynomial fitting is carried out on the brightness values of the arranged pixels, and a fitting curve is obtained;
and obtaining brightness fitting values corresponding to all pixels in the test area from the fitting curve.
With reference to the first aspect, the obtaining, for any two adjacent test areas, the standard deviation of brightness of any two adjacent test areas based on brightness values of all pixels in each test area includes:
acquiring an average brightness value of pixels in each test area based on brightness values of all pixels in each test area aiming at any two adjacent test areas;
and determining the absolute value of the difference value of the average brightness values of the pixels in the two test areas as the standard deviation of the brightness of the two adjacent test areas.
With reference to the first aspect, the obtaining the luminance unevenness determination value of the panel to be tested based on all luminance standard deviations and the luminance difference value of each pixel includes:
obtaining a target brightness difference value with an absolute value larger than a deviation threshold value from the brightness difference value of each pixel;
and determining the sum of the absolute value of each target brightness difference value and each brightness standard deviation as a brightness non-uniformity determination value of the panel to be tested.
With reference to the first aspect, the obtaining the brightness value of each pixel in the image to be processed of the panel to be tested includes:
collecting an original shooting image of a panel to be tested through a camera;
extracting a first image from the original photographed image;
downsampling the first image to obtain an image to be processed;
acquiring red, green and blue color space data of each pixel in the image to be processed;
and converting the red, green and blue color space data into color opponent space data, wherein color brightness components in the color opponent space data are brightness values of all pixels in the image to be processed.
With reference to the first aspect, the method further includes:
and under the condition that the brightness of the panel to be detected is uneven, brightness correction is carried out on the panel to be detected based on a correction unit corresponding to the type to be detected.
In a second aspect, there is provided a brightness unevenness detecting apparatus of a display panel, including:
the brightness acquisition module is used for acquiring brightness values of all pixels in the image to be processed of the panel to be tested;
the pixel extraction module is used for extracting a plurality of test areas from the image to be processed;
a brightness difference value obtaining module, configured to obtain, for each of the test areas, a brightness difference value of each pixel based on a brightness value and a brightness target value of each pixel in the test area;
the brightness standard deviation acquisition module is used for acquiring the brightness standard deviation of any two adjacent test areas based on the brightness values of all pixels in each test area aiming at any two adjacent test areas;
the judging value generating module is used for acquiring the uneven brightness judging value of the panel to be tested based on all brightness standard deviations and the brightness difference value of each pixel;
and the brightness non-uniformity judging module is used for generating a result of the brightness non-uniformity of the type to be detected of the panel to be detected under the condition that the brightness non-uniformity judging value is larger than the type threshold value corresponding to the type to be detected.
One of the above technical solutions has the following advantages or beneficial effects:
compared with the prior art, the brightness non-uniformity detection method for the display panel comprises the steps of extracting a plurality of test areas from a to-be-processed image of the panel to be detected, acquiring brightness standard deviations of any two adjacent test areas based on brightness values of each pixel in the test areas, acquiring brightness non-uniformity judgment values of the panel to be detected based on brightness difference values of each pixel and all brightness standard deviations, and generating a result that the panel to be detected has brightness non-uniformity of the type to be detected if the brightness non-uniformity judgment values are larger than a type threshold value corresponding to the type to be detected. According to the brightness non-uniformity detection method, the brightness non-uniformity of the display equipment can be automatically detected and classified, subjective influence can be avoided, the detection result can be obtained rapidly, the time for demura processing in the production process is shortened, and the production efficiency is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1a is a schematic diagram of the shape of a linear mura;
FIG. 1b is a schematic diagram of the shape of a ribbon mura;
FIG. 1c is a schematic diagram of the shape of a block mura;
FIG. 2 is a schematic diagram of a conventional method for detecting brightness unevenness of a display panel;
fig. 3 is a schematic structural diagram of a brightness non-uniformity detection system of a display panel according to an embodiment of the present application;
fig. 4 is an overall flow chart of a method for detecting brightness unevenness of a display panel according to an embodiment of the disclosure;
FIG. 5 is a schematic diagram of an example of extracting test areas in an embodiment of the present application;
FIG. 6 is another exemplary schematic diagram of an extraction test area in an embodiment of the present application;
fig. 7 is a schematic diagram of a fitted curve after the brightness values of the pixels in the embodiment of the present application are fitted;
FIG. 8 is a schematic diagram of the brightness difference of each pixel in the embodiment of the present application;
fig. 9 is a schematic flow chart of an example of a brightness non-uniformity detection method of a display panel according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a brightness non-uniformity detection device of a display panel according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. In the description of the present application, it should be understood that the terms "center," "longitudinal," "transverse," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," etc. indicate or are based on the orientation or positional relationship shown in the drawings, merely for convenience of description and to simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In this application mura refers to a defect of uneven brightness. De- "in Demura means removing the mura.
Referring to fig. 1a to 1c, fig. 1a illustrates the shape of a linear mura, fig. 1b illustrates the shape of a ribbon mura, and fig. 1c illustrates the shape of a block mura. Linear mura (A), band-like mura (B) and block-like mura (C) are the more frequently occurring mura types. Wherein, the linear mura (a) may refer to mura having an aspect ratio greater than the first threshold value α1, the band-shaped mura (B) may refer to mura having an aspect ratio greater than the second threshold value α2 and less than the first threshold value α1, and the block-shaped mura (C) may refer to mura having an aspect ratio greater than the third threshold value α3 and less than the second threshold value α2, the first threshold value α1, the second threshold value α2, and the third threshold value α3 satisfying: α3< α2< α1. When the demux process is performed in the production process of the LCD panel, the type of the mura is generally detected first.
Referring to fig. 2, fig. 2 illustrates a conventional method for detecting brightness unevenness of a display panel. In general, different levels of filters (ND filters) are placed at a distance of about 5cm (cm) from the human eye, and the human eye views an LCD Panel (LCD Panel) placed at a distance of 50cm from the different levels of filters, and finally obtains mura types based on human eye perception. However, this has subjective limitations and is time consuming to detect, affecting production time.
In view of this, the embodiment of the present application provides a method for detecting luminance unevenness of a display panel, which can avoid subjective influence and quickly obtain a detection result by providing a digital method to automatically detect and classify luminance unevenness of a display device, thereby shortening a period of performing demura processing in a production process, improving production efficiency, and solving at least part of the above technical problems.
Referring to fig. 3, fig. 3 illustrates a structure of a brightness non-uniformity detection system of a display panel according to an embodiment of the present application. The brightness unevenness detecting system includes a panel 1 to be measured, a camera 2, and a controller 3. The controller 3 is connected with the panel 1 to be tested and the camera 2 respectively, and is used for controlling the camera 2 to shoot the panel 1 to be tested and detecting mura types on the panel 1 to be tested by adopting the brightness non-uniformity detection method of the display panel in the embodiment of the application. Like this, the uneven detecting system of luminance of display panel of this application embodiment can detect mura type automatically to avoid subjective limitation to the influence of detection, can also greatly shorten detection time, improve production efficiency.
The following describes a brightness unevenness detecting method of the display panel of the embodiment of the present application.
Referring to fig. 4, fig. 4 illustrates an overall flow of a brightness non-uniformity detection method of a display panel according to an embodiment of the present application. The method for detecting the uneven brightness of the display panel comprises the following steps:
401: and acquiring brightness values of all pixels in the image to be processed of the panel to be tested.
In some embodiments, the brightness value of each pixel in the image to be processed of the panel to be tested may be obtained by:
step one, an original shooting image of a panel to be detected is acquired through a camera.
And step two, extracting a first image from the original photographed image.
Specifically, the first region may be a ROI region (Region Of Interest ), which is a focus of image analysis.
Illustratively, the first image may be extracted from the original captured image by:
first, a boundary contour is identified from an original captured image.
Wherein the boundary contour encloses the second image.
In some examples, an image segmentation technique may be employed to foreground segment the original captured image, determining the contour of the acquired foreground portion as a boundary contour.
And a second step of removing the third image from the second image to obtain the first image.
Specifically, the third image may be an edge region of the second image. The first image may be located at a center position of the second image.
By the method, the influence of uncompensated defects in the edge area on the accuracy of the detection result can be removed.
And thirdly, downsampling the first image to obtain an image to be processed.
In particular, a downsampling function may be constructed, such as: and (3) the m multiplied by m matrix, and then downsampling the first image by using a downsampling function to obtain an image to be processed. Illustratively, for a first image with a resolution of 3840×2160, downsampling with a matrix of 16×16, merging every 256 pixels into one pixel, and finally obtaining a to-be-processed image with a resolution of 240×130. Thus, the high resolution image can be compressed, the amount of data to be processed can be reduced, and the processing speed can be increased.
In some examples, the matrix size of the downsampling function is m×m, where m satisfies: m is more than or equal to 4 and less than or equal to 16. Illustratively, the matrix of the downsampling function is a range value of any one or any two of 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, 10×10, 11×11, 12×12, 13×13, 14×14, 15×15, 16×16.
By the method, the influence of the non-display area on the accuracy of the analysis result can be avoided, the processing speed can be improved, and unnecessary data participation in calculation is avoided.
In other embodiments, the original captured image of the display panel to be tested acquired by the camera may also be determined as the image to be processed of the display panel to be tested, which is not specifically limited in the embodiments of the present application.
And step four, acquiring red, green and blue color space data of each pixel in the image to be processed.
Specifically, for an image collected by a camera, the image is usually RGB (red, green and blue) chromaticity space, and the color of each pixel in the image is represented by RGB color components.
And fifthly, converting the red, green and blue color space data into color opponent space data.
Wherein the color luminance component in the color versus space data is the luminance value of each pixel in the image to be processed.
That is, each RGB color space data is converted into Lab color space data.
Specifically, first, each RGB color space data may be converted into XYZ color space data based on the following formula (1):
in formula (1), R, G and B represent data of red, green and blue components in an RGB color space, respectively, X represents a component of chromaticity of a color on a red-green axis, Y represents a luminance (brightness) component of a color, Z represents a component of chromaticity of a color on a yellow-blue axis, B 11 、b 12 、b 13 、b 21 、b 22 、b 23 、b 31 、b 32 、b 33 Is the corresponding conversion coefficient.
The XYZ color space data can then be converted to Lab color space data based on the following equation (2):
in formula (2), L is the luminance (brightness) component of the color, a is the reddish yellow level, b is the bluish green level, X, Y, Z is the color component in XYZ color space, X n 、Y n 、Z n F (t) is the conversion function for the color component corresponding to the reference white point. Wherein, L of each pixel in the image to be processed is the corresponding brightness value.
Through the mode, the CIE Lab chromaticity space is adopted to simulate the chromaticity space of human eyes, so that the human eye visual effect can be better met, and the accuracy of data processing is improved.
402: a plurality of test areas are extracted from the image to be processed.
The size of the test area is set based on the type to be detected of uneven brightness. Types of detection of brightness unevenness may include linear mura, band-shaped mura, block-shaped mura, and mura of other shapes.
Referring to fig. 5, fig. 5 illustrates an example of extracting a test area in an embodiment of the present application. In one example, the type to be detected is a first type, the test area T i Is m x n, satisfying: m=h, n=1, where H is the number of lines of the image P to be processed. Illustratively, the first type is a linear mura.
In this example, step 402 may be performed by:
each column of pixels of the image to be processed is determined as each test area. Then a plurality of test areas T i W, where W is the number of columns of the image to be processed.
For an image to be processed having a size of 240×130, for example, each column of pixels serves as one test area, 240 test areas are extracted in total, and 130 pixels are each in each test area.
In another example, the type to be detected is a first type, the test area T i Is m x n, satisfying: m=1, n=w, where W is the number of columns of the image to be processed. Illustratively, the first type is a linear mura.
In this example, step 402 may be performed by:
each row of pixels of the image to be processed is determined as each test area. Then a plurality of test areas T i And H, where H is the number of lines of the image to be processed.
For an image to be processed having a size of 240×130, as one test area per line of pixels, 130 test areas are extracted in total, with 240 pixels in each test area. Thus, a mura in a horizontal line shape can be detected.
Referring to fig. 6, fig. 6 illustrates another example of extracting a test area in an embodiment of the present application. In another example, the type to be detected is the second type, the size of the test area is m×n, satisfying: m=n, and m < min { H, W }. Or the type to be detected is a third type, the size of the test area is m multiplied by n, and the requirements are satisfied: m+.n, and the smaller of m, n is less than min { H, W }. Wherein H is the number of lines of the image to be processed, and W is the number of columns of the image to be processed. Illustratively, the second type is block mura and the third type is ribbon mura.
In this example, step 402 may be performed by:
and sequentially extracting each test area from the image to be processed by taking one column or one row as a step length until all pixels in the image to be processed are acquired. Then a plurality of test areas T i The number of (W-m) × (H-n).
Exemplary, for an image to be processed of size 240×130, the test area T i The dimensions of (2) are m×n, satisfying: m=n, and m satisfies: m is more than or equal to 8 and less than or equal to 16. Illustratively, a test area T i Is 8 x 8, 9 x 9, 10 x 10, 11 x 11, 12 x 12, 13 x 13, 14 x 14, 15 x 15, 16 x 16.
Taking 8×8 as an example, starting from the first row and first column of the image to be processed, taking the 1 st to 8 th rows and 1 st to 8 th columns of pixels as a first test area, then shifting one column backwards, taking the 1 st to 8 th rows and 2 nd to 9 th columns of pixels as a second test area, pushing the same, taking the 1 st to 8 th rows and 232 nd to 240 th columns of pixels as 232 nd test areas, then shifting one column downwards, taking the 2 nd to 9 nd rows and 232 nd to 240 nd columns of pixels as 233 nd test areas, and continuously performing cyclic extraction by taking the columns as step sizes by referring to the above mode. And (3) sequentially cycling according to the rows and the columns, and finally, circularly covering all pixel points to obtain (240-8) x (130-8) test areas. In other examples, the test regions may be sequentially extracted from any position in any order, which is not specifically limited in the embodiments of the present application.
By the method, the sizes of the test areas with different shapes and sizes can be set according to different types to be tested of the mura, so that the detection of the mura type is more targeted.
403: for each test area, acquiring a brightness difference value of each pixel based on the brightness value and the brightness target value of each pixel in the test area.
In some embodiments, the luminance difference value for each pixel may be obtained by:
step one, performing curve fitting on brightness values of all pixels in a test area aiming at each test area to obtain brightness fitting values corresponding to all pixels in the test area, wherein the brightness fitting values are brightness target values of the pixels.
Specifically, the brightness fitting value corresponding to each pixel in the test area can be obtained through the following steps:
first, all pixels in the test area are arranged according to the positions.
And secondly, performing polynomial fitting on the brightness values of the arranged pixels to obtain a fitting curve.
Specifically, the highest order of the polynomial may be determined based on the number of pixels in the test area.
And thirdly, acquiring brightness fitting values corresponding to all pixels in the test area from the fitting curve.
Referring to fig. 7, fig. 7 illustrates a fitting curve after the brightness values of the pixels are fitted in the embodiment of the present application. For an image to be processed having a size of 240×130, as one test area per line of pixels, 130 test areas are extracted in total, with 240 pixels in each test area. For 240 pixels in each test area, the brightness values of the 240 pixels (the brightness values of the respective pixels form an actual brightness array D1) may be fitted by using a curve of an 11 th order polynomial, and specifically, the fitted curve D2 may be represented by the following formula (3):
y＝p 1 ×x 11 +p 2 ×x 10 +p 3 ×x 9 +p 4 ×x 8 +p 5 ×x 7 +p 6 ×x 6 +p 7 ×x 5
+p 8 ×x 4 +p 9 ×x 3 +p 10 ×x 2 +p 11 ×x+p 12 (3)
in the formula (3), p 1 ～p 12 For the constant of the fitted curve coefficient, x is the pixel position and y is the luminance value.
And step two, acquiring the brightness difference value of each pixel based on the brightness value of each pixel and the corresponding brightness fitting value.
Referring to fig. 8, fig. 8 illustrates the brightness difference of each pixel in the embodiment of the present application. Specifically, the luminance difference value Gap of each pixel=the luminance value of each pixel-the corresponding luminance fitting value.
By the method, the fitting value can be determined to be the brightness target value, so that the target brightness has no mutation, the visual effect is better, and compared with the brightness which is regulated to be absolutely consistent, the method is simpler and easier to implement.
In other embodiments, the brightness target value may also be set according to the requirements, for example: the brightness target values of the respective pixels are all set to the same value, which is not particularly limited in the embodiment of the present application.
404: and acquiring the brightness standard deviation of any two adjacent test areas based on the brightness values of all pixels in each test area aiming at any two adjacent test areas.
In this embodiment of the present application, any two adjacent test areas refer to two adjacent test areas, or when the test areas are circularly extracted according to a certain sequence, the two adjacent test areas refer to test areas extracted sequentially. For example, when each column of pixels is taken as one test area, two adjacent test areas refer to a test area corresponding to the i-th column of pixels and a test area corresponding to the i+1-th column of pixels. For another example, when mura detection of the second type or the third type is performed, the test area is a matrix of mxn, and the test area is extracted row by row from the first column pixel of the first row, then two test areas sequentially extracted according to the extraction order may be two adjacent test areas.
Specifically, the standard deviation of brightness of any two adjacent test areas can be obtained by the following steps:
step one, for any two adjacent test areas, acquiring the average brightness value of the pixels in each test area based on the brightness values of all the pixels in each test area.
The average luminance value of the pixels in each test area can be obtained specifically by the following formula (4):
in the formula (4), d j For the average brightness value, d, of the pixels in the jth test region j+1 For the average luminance value of the pixels in the j+1th test area,for the luminance value of the ith pixel in the jth test area,/th>For the luminance value of the ith pixel in the j+1th test area, N is the total number of pixels in the test area.
And step two, determining the absolute value of the difference value of the average brightness values of the pixels in the two test areas as the standard deviation of the brightness of the two adjacent test areas.
Specifically, the standard deviation of brightness of two adjacent test areas can be determined by the following formula (5):
D＝|d j -d j+1 |(5)
in the formula (5), D is the standard deviation of brightness between the j-th test area and the j+1th test area, D j For the average brightness value, d, of the pixels in the jth test region j+1 Is the average luminance value of the pixels in the j+1th test area.
405: and acquiring the brightness non-uniformity judgment value of the panel to be tested based on all brightness standard deviations and the brightness difference value of each pixel.
In some embodiments, the luminance unevenness determination value of the panel to be measured may be obtained by:
step one, obtaining a target brightness difference value with an absolute value larger than a deviation threshold value from the brightness difference value of each pixel.
Illustratively, the deviation threshold may be set to 0.5. That is, the luminance difference value having an absolute value of less than or equal to 0.5 can be regarded as no deviation between the luminance value of the pixel and the luminance fitting value.
And step two, determining the sum of the absolute value of each target brightness difference value and each brightness standard deviation as a brightness non-uniformity determination value of the panel to be tested.
That is, the luminance unevenness determination value= Σluminance standard deviation +Σ|target luminance difference|.
It can be understood that, for the second type or the third type mura detection, since there is an overlap between the test areas, the situation that the same pixel may be located in multiple test areas may occur, in this embodiment of the present application, the fitting step is separately performed for each test area, so that the processing should be performed in units of test areas, that is, the same pixel may correspond to different brightness differences in different test areas, and if the absolute value of the brightness differences is greater than the deviation threshold, the summation operation of the brightness non-uniformity determination values should be participated.
406: and generating a result of the brightness unevenness of the type to be detected of the panel to be detected under the condition that the brightness unevenness judging value is larger than the type threshold value corresponding to the type to be detected.
In addition, when the brightness non-uniformity determination value is smaller than or equal to a type threshold value corresponding to the type to be detected, a result that the panel to be detected does not have brightness non-uniformity of the type to be detected is generated.
Illustratively, for a line mura, the corresponding type threshold may be set to 22.
It will be appreciated that in performing steps 402 to 406, a plurality of types to be detected may be sequentially performed, for example: the method comprises the steps of firstly detecting an image to be processed by using a test area corresponding to a first type, detecting the image to be processed by using a test area corresponding to a second type if the result of the brightness non-uniformity of the first type does not exist in the panel to be detected, detecting the image to be processed by using a test area corresponding to a third type if the result of the brightness non-uniformity of the second type does not exist in the panel to be detected, and the like until all the types to be detected are detected.
In addition, after performing step 406, the method of the embodiment of the present application may further include:
and under the condition that the brightness of the panel to be detected is uneven, brightness correction is carried out on the panel to be detected based on the correction unit corresponding to the type to be detected.
For example, if it is determined that the linear mura exists in the panel to be measured, brightness correction is performed on the linear mura of the panel to be measured based on the correction unit having a size of 4×16. If the block mura of the panel to be tested is determined to exist, the brightness of the block mura of the panel to be tested is corrected based on a correction unit with the size of 8 multiplied by 8. When the correction unit is used for correction, a linear interpolation mode of the related technology can be adopted, and all pixels in the corresponding range of the correction unit are corrected based on the correction data of the correction unit, so that the correction is not repeated separately.
Referring to fig. 9, fig. 9 illustrates an example flowchart of a brightness non-uniformity detection method of a display panel according to an embodiment of the present application. When the brightness unevenness of the display panel is detected, the method can firstly preprocess the image, then perform color space conversion, convert RGB color space data into Lab color space data, then circularly call test areas corresponding to different types of mura to detect, finally select a corresponding correction unit to correct the brightness if the detection meets the corresponding mura type, and end the method if the presence of the mura is not detected.
It can be appreciated that the method for detecting the brightness unevenness of the display panel can automatically detect and classify the brightness unevenness of the display device, can avoid subjective influence, and can quickly obtain a detection result, thereby shortening the time for demura processing in the production process and improving the production efficiency.
Accordingly, referring to fig. 10, fig. 10 illustrates a block diagram of a brightness non-uniformity detection apparatus for a display panel according to an embodiment of the present application. The device comprises: a luminance acquisition module 1001, a pixel extraction module 1002, a luminance difference value acquisition module 1003, a luminance standard deviation acquisition module 1004, a determination value generation module 1005, and a luminance unevenness determination module 1006. The output end of the luminance obtaining module 1001 is in communication connection with the input end of the pixel extracting module 1002, the output end of the pixel extracting module 1002 is respectively in communication connection with the input end of the luminance difference obtaining module 1003 and the input end of the luminance standard deviation obtaining module 1004, the output end of the luminance difference obtaining module 1003 and the output end of the luminance standard deviation obtaining module 1004 are both in communication connection with the input end of the determination value generating module 1005, and the output end of the determination value generating module 1005 is in communication connection with the input end of the luminance unevenness determining module 1006.
The brightness obtaining module 1001 is configured to obtain brightness values of pixels in a to-be-processed image of the panel to be tested.
The pixel extraction module 1002 is configured to extract a plurality of test areas from an image to be processed.
A luminance difference value obtaining module 1003, configured to obtain, for each test area, a luminance difference value of each pixel based on the luminance value and the luminance target value of each pixel in the test area.
The luminance standard deviation obtaining module 1004 is configured to obtain, for any two adjacent test areas, a luminance standard deviation of the any two adjacent test areas based on luminance values of all pixels in each test area.
The determination value generation module 1005 is configured to obtain a luminance unevenness determination value of the panel to be tested based on all the luminance standard deviations and the luminance difference value of each pixel.
The luminance unevenness determination module 1006 is configured to generate a result of luminance unevenness of the type to be detected of the panel to be detected when the luminance unevenness determination value is greater than a type threshold corresponding to the type to be detected.
In some embodiments, the type to be detected is a first type, the size of the test area is mxn, satisfying: m=h, n=1, where H is the number of lines of the image to be processed.
The pixel extraction module 1002 is specifically configured to:
and determining each column of pixels of the image to be processed as each test area, wherein the number of the plurality of test areas is W, and W is the number of columns of the image to be processed.
In some embodiments, the type to be detected is a second type, the size of the test area is mxn, satisfying: m=n, and m < min { H, W }. Or the type to be detected is a third type, the size of the test area is m multiplied by n, and the requirements are satisfied: m+.n, and the smaller of m, n is less than min { H, W }. Wherein H is the number of lines of the image to be processed, and W is the number of columns of the image to be processed.
The pixel extraction module 1002 is specifically configured to:
and sequentially extracting each test area from the image to be processed by taking one column or one row as a step length until all pixels in the image to be processed are acquired, wherein the number of the test areas is (W-m) x (H-n).
In some embodiments, the luminance difference value obtaining module 1003 is specifically configured to:
and performing curve fitting on the brightness values of all the pixels in the test area aiming at each test area to obtain brightness fitting values corresponding to the pixels in the test area, wherein the brightness fitting values are brightness target values of the pixels.
And acquiring the brightness difference value of each pixel based on the brightness value of each pixel and the corresponding brightness fitting value.
In some embodiments, the luminance difference value obtaining module 1003 is specifically configured to:
all pixels in the test area are arranged according to the positions.
And performing polynomial fitting on the brightness values of the arranged pixels to obtain a fitting curve.
And obtaining brightness fitting values corresponding to all pixels in the test area from the fitting curve.
In some embodiments, the luminance standard deviation obtaining module 1004 is specifically configured to:
and acquiring the average brightness value of the pixels in each test area based on the brightness values of all the pixels in each test area aiming at any two adjacent test areas.
And determining the absolute value of the difference value of the average brightness values of the pixels in the two test areas as the standard deviation of brightness of the two adjacent test areas.
In some embodiments, the decision value generation module 1005 is specifically configured to:
from the luminance difference value of each pixel, a target luminance difference value having an absolute value larger than the deviation threshold value is obtained.
And determining the sum of the absolute value of each target brightness difference value and each brightness standard deviation as a brightness non-uniformity determination value of the panel to be tested.
In some embodiments, the luminance acquisition module 1001 is specifically configured to:
and acquiring an original shooting image of the panel to be tested through a camera.
The first image is extracted from the original photographed image.
And downsampling the first image to obtain an image to be processed.
Red, green and blue color space data of each pixel in the image to be processed are acquired.
The red, green and blue color space data are converted into color opponent space data, and color brightness components in the color opponent space data are brightness values of all pixels in the image to be processed.
In some embodiments, the apparatus further comprises:
the brightness correction module is used for carrying out brightness correction on the panel to be detected based on the correction unit corresponding to the type to be detected under the condition that the panel to be detected has uneven brightness of the type to be detected.
It can be appreciated that the uneven brightness detection device of the display panel of the embodiment of the application can automatically detect and classify uneven brightness of the display device, can avoid subjective influence, and can quickly obtain a detection result, thereby shortening the time for demura processing in the production process and improving the production efficiency.
The foregoing describes in detail the method and apparatus for detecting luminance unevenness of a display panel provided in the embodiments of the present application, and specific examples are applied to describe the principles and embodiments of the present application, where the descriptions of the foregoing examples are only used to help understand the technical solutions and core ideas of the present application; those of ordinary skill in the art will appreciate 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 of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A method for detecting luminance unevenness of a display panel, comprising:
acquiring brightness values of pixels in an image to be processed of a panel to be tested;
extracting a plurality of test areas from the image to be processed;
for each test area, acquiring a brightness difference value of each pixel based on a brightness value and a brightness target value of each pixel in the test area;
acquiring brightness standard deviations of any two adjacent test areas based on brightness values of all pixels in each test area aiming at any two adjacent test areas;
acquiring a brightness non-uniformity judgment value of the panel to be tested based on all brightness standard deviations and the brightness difference value of each pixel;
and generating a result of the brightness unevenness of the type to be detected of the panel to be detected under the condition that the brightness unevenness judging value is larger than a type threshold value corresponding to the type to be detected.
2. The method for detecting luminance unevenness of a display panel according to claim 1, wherein the type to be detected is a first type, and the size of the test area is m×n, satisfying: m=h, n=1, where H is the number of lines of the image to be processed;
extracting a plurality of test areas from the image to be processed, including:
and determining each column of pixels of the image to be processed as each test area, wherein the number of the test areas is W, and W is the number of columns of the image to be processed.
3. The method for detecting luminance unevenness of a display panel according to claim 1, wherein the type to be detected is a second type, and the size of the test area is m×n, satisfying: m=n, and m < min { H, W }; or the type to be detected is a third type, and the size of the test area is m×n, so that the following conditions are satisfied: m is not equal to n, and the smaller of m and n is smaller than min { H, W }; wherein H is the number of rows of the image to be processed, and W is the number of columns of the image to be processed;
extracting a plurality of test areas from the image to be processed, including:
and sequentially extracting each test area from the image to be processed by taking one column or one row as a step length until all pixels in the image to be processed are acquired, wherein the number of the plurality of test areas is (W-m) x (H-n).
4. The method for detecting luminance unevenness of a display panel according to any one of claims 1 to 3, wherein the obtaining, for each of the test regions, a luminance difference value for each pixel based on a luminance value and a luminance target value for each pixel within the test region, comprises:
performing curve fitting on brightness values of all pixels in the test area aiming at each test area to obtain brightness fitting values corresponding to all pixels in the test area, wherein the brightness fitting values are the brightness target values of the pixels;
and acquiring the brightness difference value of each pixel based on the brightness value of each pixel and the corresponding brightness fitting value.
5. The method for detecting luminance unevenness of a display panel according to claim 4, wherein performing curve fitting on luminance values of all pixels in the test area to obtain luminance fitting values corresponding to each pixel in the test area, comprises:
arranging all pixels in the test area according to the positions;
polynomial fitting is carried out on the brightness values of the arranged pixels, and a fitting curve is obtained;
and obtaining brightness fitting values corresponding to all pixels in the test area from the fitting curve.
6. The method for detecting luminance unevenness of a display panel according to any one of claims 1 to 3, wherein the obtaining, for any two adjacent test regions, a luminance standard deviation of any two adjacent test regions based on luminance values of all pixels in each of the test regions, comprises:
acquiring an average brightness value of pixels in each test area based on brightness values of all pixels in each test area aiming at any two adjacent test areas;
and determining the absolute value of the difference value of the average brightness values of the pixels in the two test areas as the standard deviation of the brightness of the two adjacent test areas.
7. The method for detecting luminance unevenness of a display panel according to claim 6, wherein the obtaining the luminance unevenness determination value of the panel to be detected based on all luminance standard deviations and the luminance difference value of each pixel comprises:
obtaining a target brightness difference value with an absolute value larger than a deviation threshold value from the brightness difference value of each pixel;
and determining the sum of the absolute value of each target brightness difference value and each brightness standard deviation as a brightness non-uniformity determination value of the panel to be tested.
8. The method for detecting luminance unevenness of a display panel according to claim 1, wherein the obtaining the luminance value of each pixel in the image to be processed of the panel to be detected includes:
collecting an original shooting image of a panel to be tested through a camera;
extracting a first image from the original photographed image;
downsampling the first image to obtain an image to be processed;
acquiring red, green and blue color space data of each pixel in the image to be processed;
and converting the red, green and blue color space data into color opponent space data, wherein color brightness components in the color opponent space data are brightness values of all pixels in the image to be processed.
9. The method of detecting luminance unevenness of a display panel according to claim 1, further comprising:
and under the condition that the brightness of the panel to be detected is uneven, brightness correction is carried out on the panel to be detected based on a correction unit corresponding to the type to be detected.
10. A brightness unevenness detecting device of a display panel, comprising:
the brightness acquisition module is used for acquiring brightness values of all pixels in the image to be processed of the panel to be tested;
the pixel extraction module is used for extracting a plurality of test areas from the image to be processed;
a brightness difference value obtaining module, configured to obtain, for each of the test areas, a brightness difference value of each pixel based on a brightness value and a brightness target value of each pixel in the test area;
the brightness standard deviation acquisition module is used for acquiring the brightness standard deviation of any two adjacent test areas based on the brightness values of all pixels in each test area aiming at any two adjacent test areas;
the judging value generating module is used for acquiring the uneven brightness judging value of the panel to be tested based on all brightness standard deviations and the brightness difference value of each pixel;
and the brightness non-uniformity judging module is used for generating a result of the brightness non-uniformity of the type to be detected of the panel to be detected under the condition that the brightness non-uniformity judging value is larger than the type threshold value corresponding to the type to be detected.
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