CN118707785B - Quick automatic exposure method and device for display screen Demura and storage medium - Google Patents
Quick automatic exposure method and device for display screen Demura and storage medium Download PDFInfo
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03B—APPARATUS OR ARRANGEMENTS FOR TAKING PHOTOGRAPHS OR FOR PROJECTING OR VIEWING THEM; APPARATUS OR ARRANGEMENTS EMPLOYING ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ACCESSORIES THEREFOR
- G03B7/00—Control of exposure by setting shutters, diaphragms or filters, separately or conjointly
- G03B7/08—Control effected solely on the basis of the response, to the intensity of the light received by the camera, of a built-in light-sensitive device
- G03B7/091—Digital circuits
- G03B7/093—Digital circuits for control of exposure time
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
- G09G2320/00—Control of display operating conditions
- G09G2320/02—Improving the quality of display appearance
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Abstract
The application discloses a rapid automatic exposure method, a rapid automatic exposure device and a storage medium for a display screen Demura, which are used for reducing iteration time and improving operation efficiency. The application comprises the following steps: acquiring a picture to be acquired, and setting actual brightness and target gray level for the picture to be acquired; calculating initial exposure time through the actual brightness, the target gray scale and the exposure time model; adjusting the camera by using the calculated initial exposure time, and inputting the corresponding picture to be acquired into a display screen to be detected; using a camera to acquire images of a display screen to be tested, and generating display screen acquired images; carrying out histogram analysis on the acquired image of the display screen, and generating a histogram mean value according to the histogram analysis result; performing standard analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen; if the exposure time does not reach the standard, correcting the initial exposure time, and re-collecting and analyzing; if the acquired images reach the standard, switching to the next image to be acquired for analysis.
Description
Technical Field
The embodiment of the application relates to the field of display screen detection, in particular to a rapid automatic exposure method, a rapid automatic exposure device and a storage medium of a display screen Demura.
Background
With the development of industry and internet technology, the requirements of industry on the quality of industrial products are more and more refined and standardized, and the quality of the products directly affects the competitiveness of the products in terms of the display panel industry.
A display screen is used as one of display components of a device, and is applied to various high-end devices, such as a mobile phone, a television, a tablet computer, and the like. With the increasing demands of people on picture display, display screens gradually become technically precise products.
In the field of display screen manufacturing, demura is an important process step for correcting brightness uniformity and chromaticity uniformity of each pixel point on a display screen so as to ensure accuracy and consistency of a display image. In the field of display screen manufacturing, good imaging quality is the basis for performing Demura and defect detection analysis, which directly affects the accuracy of the detection process. In the case of imaging device determination, however, exposure is a key variable affecting the imaging quality of the camera.
Currently, the control of the exposure of a camera generally depends on manual adjustment of exposure parameters, which is time-consuming and labor-consuming and is easily affected by human factors. The existing automatic exposure technology based on display screen vision processing is generally realized by the principle of iterative approximation through multiple exposure mapping analysis according to set target gray level. However, for the case of a lower gray-scale frame or an unreasonable initial exposure time setting, the iteration times will increase, and such a processing manner will increase the iteration time and reduce the operation efficiency.
Disclosure of Invention
The application discloses a rapid automatic exposure method, a rapid automatic exposure device and a storage medium for a display screen Demura, which are used for reducing iteration time and improving operation efficiency.
The first aspect of the present application discloses a method for rapid automatic exposure of a display screen Demura, comprising:
acquiring a plurality of pictures to be acquired, setting actual brightness for each picture to be acquired, and setting target gray scale of a display screen acquisition image corresponding to the picture to be acquired;
Inputting the actual brightness and the target gray scale into an exposure time model, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated after the brightness, the gray scale and the exposure time are calibrated by a camera under the current working condition;
Adjusting the camera by using the calculated initial exposure time, and inputting the corresponding picture to be acquired into a display screen to be detected;
using a camera to acquire images of a display screen to be tested, and generating display screen acquired images;
Carrying out histogram analysis on the acquired image of the display screen, and generating a histogram mean value according to the histogram analysis result;
performing standard analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen;
if the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time;
If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
Optionally, before acquiring a plurality of frames to be acquired, setting actual brightness for each frame to be acquired, and setting target gray scale of an image acquired by a display screen corresponding to the frame to be acquired, the rapid automatic exposure method further includes:
Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring a first calibration image of the calibration display screen through a camera;
Calculating the brightness average value of the central area of the display screen according to the first image data of the first calibration image;
setting an upper gray level limit and a lower gray level limit;
determining the corresponding exposure time range of the camera through the upper gray level limit and the lower gray level limit;
acquiring at least two second calibration images within an exposure time range by using a camera;
Calculating the gray average value of each second calibration image in the central area according to the second image data of the second calibration image;
Fitting is carried out according to the exposure time of the camera, the brightness average value of the central area of the display screen and the gray average value of the second calibration image in the central area, and an exposure time model of the camera under the current working condition is generated.
Optionally, determining the exposure time range corresponding to the camera through the upper gray level limit and the lower gray level limit includes:
Shooting the calibration display screen through a camera, and adjusting the exposure time of the camera in the shooting process to generate a third calibration image;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level upper limit, determining the current exposure time as the first exposure time;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level lower limit, determining the current exposure time as the second exposure time, wherein the first exposure time and the second exposure time form an exposure time range.
Optionally, capturing at least two second calibration images over an exposure time range using a camera, including:
determining an exposure time acquisition interval according to the exposure time range;
Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring images by using a camera according to the exposure time acquisition interval to generate a second calibration image.
Optionally, performing histogram analysis on the acquired image of the display screen, and generating a histogram mean according to a result of the histogram analysis, including:
dividing gray levels for the acquired images of the display screen and determining the number of the gray levels;
Determining frequency distribution data of each gray level for the acquired image of the display screen;
determining the total number of pixels of the acquired image of the display screen;
And calculating the histogram mean value of the acquired image of the display screen according to the number of gray levels, the frequency distribution data of each gray level and the total number of pixels.
Optionally, dividing the gray level for the acquired image of the display screen and determining the number of gray levels includes:
Acquiring gray value data of each pixel point in an acquired image of a display screen;
performing regional pixel attention calculation for pixel points of the acquired image of the display screen according to the gray value data to generate regional attention data;
Dividing attention areas with different gray levels on the acquired images of the display screen according to the regional attention data;
Generating an attention matrix for edge pixel points among different attention areas according to the gray value data, and generating an area attention matrix;
Dividing different gray levels of pixel points in the attention area according to the area attention matrix;
the number of gray levels of the two divisions is determined.
The second aspect of the present application discloses a rapid automatic exposure apparatus for a display screen Demura, comprising:
The acquisition unit is used for acquiring a plurality of pictures to be acquired, setting actual brightness for each picture to be acquired, and setting target gray level of an acquired image of a display screen corresponding to the picture to be acquired;
The first calculation unit is used for inputting the actual brightness and the target gray scale into an exposure time model, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated after the brightness, the gray scale and the exposure time are calibrated by the camera under the current working condition;
the adjusting unit is used for adjusting the camera by using the calculated initial exposure time and inputting the corresponding picture to be acquired into the display screen to be detected;
the first generation unit is used for acquiring images of the display screen to be tested by using the camera and generating display screen acquired images;
The second generation unit is used for carrying out histogram analysis on the acquired images of the display screen and generating a histogram mean value according to the histogram analysis result;
the analysis unit is used for carrying out standard analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen;
The correction unit is used for correcting the initial exposure time according to the target gray level and the histogram mean value if the histogram mean value does not reach the standard, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time;
And the first determining unit is used for determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified if the mean value of the histogram is in the preset range, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
Optionally, before the acquiring unit, the rapid auto-exposure apparatus further includes:
the first acquisition unit is used for inputting the maximum gray-scale picture into the calibration display screen for display, and acquiring a first calibration image of the calibration display screen through the camera;
The second calculating unit is used for calculating the brightness average value of the central area of the display screen according to the first image data of the first calibration image;
A setting unit configured to set an upper gray level limit and a lower gray level limit;
a second determining unit, configured to determine an exposure time range corresponding to the camera through an upper gray level limit and a lower gray level limit;
the second acquisition unit is used for acquiring at least two second calibration images in the exposure time range by using the camera;
the third calculation unit is used for calculating the gray average value of each second calibration image in the central area according to the second image data of the second calibration images;
The third generating unit is used for fitting according to the exposure time of the camera, the brightness average value of the central area of the display screen and the gray average value of the second calibration image in the central area, and generating an exposure time model of the camera under the current working condition.
Optionally, the second determining unit includes:
Shooting the calibration display screen through a camera, and adjusting the exposure time of the camera in the shooting process to generate a third calibration image;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level upper limit, determining the current exposure time as the first exposure time;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level lower limit, determining the current exposure time as the second exposure time, wherein the first exposure time and the second exposure time form an exposure time range.
Optionally, the second acquisition unit includes:
determining an exposure time acquisition interval according to the exposure time range;
Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring images by using a camera according to the exposure time acquisition interval to generate a second calibration image.
Optionally, the second generating unit includes:
The first determining module is used for dividing gray levels for the acquired images of the display screen and determining the number of the gray levels;
the second determining module is used for determining the frequency distribution data of each gray level for the acquired image of the display screen;
A third determining module, configured to determine a total number of pixels of the image acquired by the display screen;
and the calculation module is used for calculating the histogram mean value of the acquired image of the display screen according to the number of gray levels, the frequency distribution data of each gray level and the total number of pixels.
Optionally, the first determining module includes:
Acquiring gray value data of each pixel point in an acquired image of a display screen;
performing regional pixel attention calculation for pixel points of the acquired image of the display screen according to the gray value data to generate regional attention data;
Dividing attention areas with different gray levels on the acquired images of the display screen according to the regional attention data;
Generating an attention matrix for edge pixel points among different attention areas according to the gray value data, and generating an area attention matrix;
Dividing different gray levels of pixel points in the attention area according to the area attention matrix;
the number of gray levels of the two divisions is determined.
A third aspect of the present application provides a rapid auto-exposure apparatus for a display screen Demura, comprising:
a processor, a memory, an input-output unit, and a bus;
the processor is connected with the memory, the input/output unit and the bus;
The memory holds a program that the processor invokes to perform any of the optional fast auto-exposure methods as in the first aspect as well as the first aspect.
A fourth aspect of the application provides a computer readable storage medium having a program stored thereon, which when executed on a computer performs the optional fast auto-exposure method of the first aspect as well as the first aspect.
From the above technical solutions, the embodiment of the present application has the following advantages:
In the application, a plurality of pictures to be acquired are firstly acquired, the actual brightness of each picture to be acquired is set, and the target gray level of the acquired image of the display screen corresponding to the picture to be acquired is set. The method comprises the steps of inputting actual brightness and target gray scale into an exposure time model generated by a camera, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated by calibrating the brightness, the gray scale and the exposure time of the camera under the current working condition. The calculated initial exposure time is used for adjusting the camera, the corresponding picture to be acquired is input into the display screen to be detected, and the initial exposure time is not necessarily the optimal exposure time but is relatively close to the optimal exposure time. And acquiring images of the display screen to be tested by using a camera, and generating display screen acquired images. And carrying out histogram analysis on the acquired image of the display screen, acquiring different gray level data in the acquired image of the display screen as analysis results, and calculating corresponding histogram average values according to the histogram analysis results. And carrying out standard reaching analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen. If the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time. If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
The method comprises the steps of calibrating an industrial-level camera used in a Demura process in advance, establishing a mathematical model between brightness, gray scale and exposure time, and then calculating the initial exposure time of a gray scale picture to be shot according to the exposure time model, the set brightness of a required gray scale picture (picture to be acquired) and the target gray scale of a display screen acquired image corresponding to the picture to be acquired. And adjusting the camera by using the calculated initial exposure time, acquiring a picture to be detected displayed on the display screen by the camera, carrying out gray level histogram analysis on the acquired display screen acquired image, judging whether the gray level on the display screen acquired image is qualified or not, further determining whether the exposure time is in conformity or not, and if the gray level is not qualified, further correcting and adjusting the exposure time by using the target gray level and the histogram mean value of the display screen acquired image, thereby realizing the rapid automatic exposure of the camera in the process of the display screen Demura. According to the method, manual adjustment is not needed, and the initial exposure time is corrected in an auxiliary mode through histogram analysis, gray level and histogram mean value, so that the exposure time adjustment times are greatly reduced, the iteration time is reduced, and the operation efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being 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. 1 is a schematic diagram of a method for rapid auto-exposure of a display screen Demura according to one embodiment of the present application;
FIG. 2 is a schematic diagram of a first stage of a rapid auto-exposure method for a display Demura according to one embodiment of the present application;
FIG. 3 is a schematic diagram of a second stage of the fast auto-exposure method of the display Demura according to one embodiment of the present application;
FIG. 4 is a schematic diagram of an embodiment of a third stage of the fast auto-exposure method of the display Demura of the present application;
FIG. 5 is a schematic view of an embodiment of a rapid auto-exposure apparatus of a display screen Demura according to the present application;
Fig. 6 is a schematic diagram of another embodiment of a rapid auto-exposure apparatus for a display Demura according to the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]". Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
The Demura process in the field of display screen manufacturing is an important process step, and is mainly used for correcting the brightness uniformity and chromaticity uniformity of each pixel point on a display screen so as to ensure the accuracy and consistency of a display image. In the field of display screen manufacturing, good imaging quality is the basis for performing Demura and defect detection analysis, which directly affects the accuracy of the detection process. In the case of imaging device determination, however, exposure is a key variable affecting the imaging quality of the camera. In the prior art, the control of the exposure of the camera generally depends on manual adjustment of exposure parameters, which is time-consuming and labor-consuming and is easily affected by human factors. The existing automatic exposure technology based on display screen vision processing is generally realized by the principle of iterative approximation through multiple exposure mapping analysis according to set target gray level. However, for the case of a lower gray-scale frame or an unreasonable initial exposure time setting, the iteration times will increase, and such a processing manner will increase the iteration time and reduce the operation efficiency.
Based on the above, the application discloses a rapid automatic exposure method, a rapid automatic exposure device and a storage medium for a display screen Demura, which are used for reducing iteration time and improving operation efficiency.
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The method of the present application may be applied to a server, a device, a terminal, or other devices having logic processing capabilities, and the present application is not limited thereto. For convenience of description, the following description will take an execution body as an example of a terminal.
Referring to fig. 1, the present application provides an embodiment of a method for fast and automatic exposure of a display screen Demura, which includes:
101. acquiring a plurality of pictures to be acquired, setting actual brightness for each picture to be acquired, and setting target gray scale of a display screen acquisition image corresponding to the picture to be acquired;
In this embodiment, the shooting module, the display screen to be tested, the crimping device and other devices are all set under the darkroom condition, and the shooting module is composed of an industrial-level camera (a visible light band, the camera comprises a flat field correction function and is started in the calibration and measurement process), a tele industrial lens, a man-machine interaction interface, a computer, a display screen controller and the like.
In this embodiment, the terminal first obtains a plurality of adaptive frames to be collected according to the model of the display screen to be measured, and then sets the actual brightness of each frame to be collected(Generally, the brightness value of the display screen of the same model which is adjusted to Pgamma on the same gray-scale picture is basically stable and can be measured during calibration), and the corresponding display screen acquires the target gray scale of the image。
102. Inputting the actual brightness and the target gray scale into an exposure time model, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated after the brightness, the gray scale and the exposure time are calibrated by a camera under the current working condition;
the terminal inputs the actual brightness and the target gray level into a camera calibrated exposure time model, so as to calculate the initial exposure time of the picture to be acquired, and record the initial exposure time as . The exposure time model is an initial exposure time calculation model generated after the camera calibrates brightness, gray scale and exposure time under the current working condition, and has the function of reducing initial errors so as to reduce adjustment times, wherein the initial exposure time can be close to the optimal exposure time as much as possible in actual operation.
It should be noted that the camera needs to be set to the same working environment during the calibration process and the actual operation process, which is beneficial to reducing the error of the initial exposure time caused by the working environment difference.
103. Adjusting the camera by using the calculated initial exposure time, and inputting the corresponding picture to be acquired into a display screen to be detected;
the terminal firstly selects a picture to be acquired, and according to the calculated initial exposure time of the picture to be acquired The camera is adjusted, and the picture to be acquired is input into the display screen to be detected, so that the display screen to be detected displays the picture.
104. Using a camera to acquire images of a display screen to be tested, and generating display screen acquired images;
When the terminal adjusts the initial exposure time of the camera and inputs the picture to be acquired into the display screen to be detected, the camera can be used for acquiring the image of the display screen to be detected, and a corresponding display screen acquisition image is generated.
105. Carrying out histogram analysis on the acquired image of the display screen, and generating a histogram mean value according to the histogram analysis result;
the terminal performs histogram analysis on the acquired images of the display screen so that the gray level of the acquired images of the display screen can be analyzed, and the histogram mean value is obtained through calculation after the gray level is determined.
A histogram is an image analysis tool that represents the frequency distribution of the various gray levels in an image. The frequency of each gray level represents the number of times or the proportion of occupation of that gray level in the sampled image of the display screen. The histogram mean is calculated by multiplying each gray level by its corresponding frequency, then adding all the calculated parameter products and dividing by the total number of pixels N of the image. The formula is as follows:
wherein: The number of gray levels representing the image (e.g., an 8bit image, L may be set to 256), Representing gray scale levelsThe frequency of occurrence in the image, N represents the total number of pixels of the image,Representing the histogram mean of the image.
106. Performing standard analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen;
According to the histogram analysis principle and the histogram mean calculation mode in the previous steps, determining the region of the display screen ROI (for example, the region of the display screen 500 x 500 image can be set manually, and is not limited) in the acquired image of the display screen, and performing histogram analysis, and calculating to obtain the histogram mean. Detecting whether the average value of the histogram is at the set image target gray level Within a determined range, for example: and (0.9 Gg,1.1 Gg), if the gray level of the acquired image of the display screen is judged to reach the standard in the range, the exposure time can be determined to be in accordance with the condition.
107. If the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time;
if the gray level of the acquired image of the display screen does not reach the standard, the current initial exposure time is required to be corrected, and the initial exposure time is required to be corrected Correcting to obtain corrected exposure time of the picture to be acquiredTarget gray level of image acquired by using display screenThe correction coefficient is calculated as follows:
The formula is used for correcting target gray scale of a display screen acquisition image of which the coefficient is to be set Dividing by gray histogram meanGenerating correction coefficients and then multiplying the correction coefficients by the initial exposure timeObtaining corrected exposure time of the picture to be acquiredAfter the initial exposure time has been corrected, it is necessary to continue repeating steps 104 to 106 until the histogram means is met.
108. If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
When the histogram mean value of the pictures to be acquired is qualified, indicating that the current detection is completed, inputting the next picture to be acquired is needed, and then repeating the steps 103 to 106 until all the pictures to be acquired are processed.
In this embodiment, a plurality of frames to be acquired are acquired first, actual brightness is set for each frame to be acquired, and target gray scale of an image acquired by a display screen corresponding to the frame to be acquired is set. The method comprises the steps of inputting actual brightness and target gray scale into an exposure time model generated by a camera, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated by calibrating the brightness, the gray scale and the exposure time of the camera under the current working condition. The calculated initial exposure time is used for adjusting the camera, the corresponding picture to be acquired is input into the display screen to be detected, and the initial exposure time is not necessarily the optimal exposure time but is relatively close to the optimal exposure time. And acquiring images of the display screen to be tested by using a camera, and generating display screen acquired images. And carrying out histogram analysis on the acquired image of the display screen, acquiring different gray level data in the acquired image of the display screen as analysis results, and calculating corresponding histogram average values according to the histogram analysis results. And carrying out standard reaching analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen. If the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time. If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
The method comprises the steps of calibrating an industrial-level camera used in a Demura process in advance, establishing a mathematical model between brightness, gray scale and exposure time, and then calculating the initial exposure time of a gray scale picture to be shot according to the exposure time model, the set brightness of a required gray scale picture (picture to be acquired) and the target gray scale of a display screen acquired image corresponding to the picture to be acquired. And adjusting the camera by using the calculated initial exposure time, acquiring a picture to be detected displayed on the display screen by the camera, carrying out gray level histogram analysis on the acquired display screen acquired image, judging whether the gray level on the display screen acquired image is qualified or not, further determining whether the exposure time is in conformity or not, and if the gray level is not qualified, further correcting and adjusting the exposure time by using the target gray level and the histogram mean value of the display screen acquired image, thereby realizing the rapid automatic exposure of the camera in the process of the display screen Demura. According to the method, manual adjustment is not needed, and the initial exposure time is corrected in an auxiliary mode through histogram analysis, gray level and histogram mean value, so that the exposure time adjustment times are greatly reduced, the iteration time is reduced, and the operation efficiency is improved.
Referring to fig. 2, 3 and 4, another embodiment of a method for rapid auto-exposure of a display screen Demura is provided, which includes:
201. Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring a first calibration image of the calibration display screen through a camera;
202. calculating the brightness average value of the central area of the display screen according to the first image data of the first calibration image;
203. Setting an upper gray level limit and a lower gray level limit;
In this embodiment, the Demura system and the calibration display screen (adjusted Pgamma) are placed in a darkroom working environment, the working states of the camera gain, the camera working distance, the lens aperture and the lens focal length are kept unchanged when the model of the corresponding display screen is normal Demura, a computer sends power-on and image-cutting instructions to a display screen controller, the maximum gray-scale image is input into the calibration display screen to be lightened and displayed, the display screen displays a gray-scale W 255 image, and a first calibration image of the calibration display screen is acquired through the camera.
The terminal calculates the average brightness value of the central area of the display screen according to the first image data of the first calibration image, specifically, the terminal measures the brightness of the central area of the display screen by using a handheld color analyzer (for example, 410), takes an average value after measuring for a plurality of times, and marks the measured average brightness value of the central area of the display screen of the W 255 picture as L 255.
Next, the terminal sets an upper gray level limit and a lower gray level limit, specifically, the camera is started to photograph the display screen to be tested, and the upper gray level limit and the lower gray level limit are respectively set to be 85% and 5% of the maximum gray level value of the image (for example, 255 for an 8bit image).
204. Shooting the calibration display screen through a camera, and adjusting the exposure time of the camera in the shooting process to generate a third calibration image;
205. when the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level upper limit, determining the current exposure time as the first exposure time;
206. when the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level lower limit, determining the current exposure time as the second exposure time, wherein the first exposure time and the second exposure time form an exposure time range;
After the terminal sets the upper gray level limit and the lower gray level limit, the terminal shoots the calibration display screen through the camera, the exposure time of the camera is continuously adjusted in the shooting process, a plurality of third calibration images are generated, the gray level of the third calibration images is determined, when the gray level of the third calibration images shot by the camera is located in the gray level range determined by the upper gray level limit, the current exposure time is determined to be the first exposure time, when the gray level of the third calibration images shot by the camera is located in the gray level range determined by the lower gray level limit, the current exposure time is determined to be the second exposure time, and the first exposure time and the second exposure time form an exposure time range. Specifically, the terminal uses the camera automatic exposure function or manually adjusts the camera exposure to make the image gray level collected by the camera near the set target gray level, and marks the camera exposure time corresponding to the two target gray levels as a second exposure time t low and a first exposure time t high, respectively, with the unit of ms.
207. Determining an exposure time acquisition interval according to the exposure time range;
208. Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring images by using a camera according to the acquisition interval of exposure time to generate a second calibration image;
In this embodiment, the terminal sets the second exposure time t low as the initial exposure time of the camera, the first exposure time t high as the final exposure time of the camera, and n as the number of calibration acquired images (i.e. the number of images to be acquired set in the calibration process is preferably 50 or more, and is not limited by the above, and the exposure time interval t step, i.e. t step=(thigh-tlow)/(n-1) can be calculated according to the above data.
And the terminal inputs the maximum gray-scale picture into the calibration display screen for display, and uses the camera to acquire images according to the exposure time acquisition interval to generate a plurality of second calibration images.
Specifically, the fixed calibration display screen displays the W 255 picture, the camera is used to photograph the display screen, the exposure time of the camera is set to be changed gradually from t low, each time an image is taken after t step is added until the exposure time of the camera reaches t high (the exposure time can be changed gradually from t high, each time an image is taken after t step is reduced), and the corresponding exposure time of each image when the camera takes a photograph is recorded, for example T={T0=tlow,T1=tlow+tstep,T2=tlow+2*tstep,…,T79=thigh}.
209. Calculating the gray average value of each second calibration image in the central area according to the second image data of the second calibration image;
210. Fitting is carried out according to the exposure time of the camera, the brightness average value of the central area of the display screen and the gray average value of the second calibration image in the central area, and an exposure time model of the camera under the current working condition is generated;
In this embodiment, the terminal calculates the gray average value of each second calibration image in the central area according to the second image data of the second calibration images, specifically, the terminal calculates the gray average value by taking a rectangular area (the area can be calculated according to the field angle of the camera lens and the size of the camera chip) of the image data with respect to the field of view of 2 ° of the center of the optical axis of the camera, and obtains the central gray average value { G t |t e T } of the central area of the image.
Then, the terminal fits according to the exposure time of the camera, the brightness average value of the central area of the display screen and the central gray average value to generate an exposure time model of the camera under the current working condition, specifically, the terminal uses the brightness L 255 of the central area of the picture of the calibration display screen W 255, the central gray average value { G t |t epsilon T } of the central area of the picture and the exposure time sequence T={T0=tlow,T1=tlow+tstep,T2=tlow+2*tstep,…,T79=thigh} corresponding to the calibration picture to perform least square fitting (linear fitting or polynomial fitting) so as to obtain the brightness model of the camera under the working condition. Using a linear fit, a camera exposure time model can be obtained:
wherein, In order for the brightness to be high,In order for the exposure time to be within the desired range,AndIn order to fit the coefficients of the coefficients,Is the gray average value.
211. Acquiring a plurality of pictures to be acquired, setting actual brightness for each picture to be acquired, and setting target gray scale of a display screen acquisition image corresponding to the picture to be acquired;
212. inputting the actual brightness and the target gray scale into an exposure time model, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated after the brightness, the gray scale and the exposure time are calibrated by a camera under the current working condition;
213. adjusting the camera by using the calculated initial exposure time, and inputting the corresponding picture to be acquired into a display screen to be detected;
214. using a camera to acquire images of a display screen to be tested, and generating display screen acquired images;
Steps 211 to 214 in this embodiment are similar to steps 101 to 104 in the previous embodiment, and are not repeated here.
215. Acquiring gray value data of each pixel point in an acquired image of a display screen;
216. performing regional pixel attention calculation for pixel points of the acquired image of the display screen according to the gray value data to generate regional attention data;
217. dividing attention areas with different gray levels on the acquired images of the display screen according to the regional attention data;
218. Generating an attention matrix for edge pixel points among different attention areas according to the gray value data, and generating an area attention matrix;
219. dividing different gray levels of pixel points in the attention area according to the area attention matrix;
220. determining the number of gray levels divided twice;
In this embodiment, the kernel of the histogram analysis is that the gray level needs to be classified, the frame to be acquired is different from the conventional display frame, in order to correct the distortion of the pixels, the frame to be acquired often needs to set dot matrix points, each dot matrix in the dot matrix point image includes a plurality of pixel points, and the gray level of the pixel points in the dot matrix points is different from the gray level of the pixel points in the background area. Such pictures to be acquired are also called calibration pictures. The gray scale of such an image does not need to use a dense gray scale, and if the gray scale L is 256 as in embodiment 1, there is a problem that the operation amount is excessively large. In an actual scene, the terminal calculates regional pixel attention for the pixel points of the acquired image of the display screen according to the gray value data by acquiring the gray value data of each pixel point in the acquired image of the display screen, generates regional attention data, specifically, the regional pixel attention is firstly divided into regions with larger difference, the gray scales of the image to be acquired are very different among the regions due to the characteristics of the image to be acquired of the display screen, the gray scales in the dot matrix point regions are almost the same, the gray scales outside the dot matrix point regions are basically similar, and therefore the regional pixel attention can be firstly divided according to the regions.
The regional pixel attention module RPA in this embodiment is formed by sequentially connecting BatchNorm-DefConv-ReLU, batchNorm-DefConv, sigMoid function modules and bilinear interpolation modules in series. It should be noted that, the BatchNorm-DefConv-ReLU layer and the BatchNorm-DefConv layer belong to the pixel feature processing layer, and the SigMoid function is a preset function. The regional pixel attention module RPA is used as a regional attention mechanism and is used for distributing a weight to each regional pixel on the acquired image of the display screen, so that the characteristics of similar pixel points are enhanced, and the regions formed by the similar pixel points can be focused more.
Next, the terminal divides the attention areas of different gray levels on the display screen captured image according to the area attention data, i.e. categorizes the areas with similar gray levels, because the areas with similar pixels are very similar in attention.
After the primary region attention division is performed, the divided regions can be subjected to primary division of gray levels, but on the edge between two regions of the acquired image of the display screen, gray level gradual change may exist, at this time, attention calculation needs to be performed on the part of pixel points, a corresponding attention matrix is generated, attention matrix generation is performed on the pixel points in the attention region according to gray value data, a region attention matrix is generated, specifically, only the edge pixel points need to be subjected to attention calculation, and no decimal point refers to N rows of pixel points located between the two regions, wherein the N rows of pixel points comprise some pixel points inside the two regions.
Specifically, the attention matrix in this embodiment is generated by using a Dropout module ADO, which includes BatchNorm-2 x 2defconv-ReLU and BatchNorm-2 x 2defconv-SigMiod. The attention-based Dropout method is different from a random manner used by general dropouts, and in this embodiment, the attention is used to determine whether the relationship between edge pixel points belongs to a gradual change relationship or an abrupt change relationship.
The input edge area is put into BatchNorm-2 x 2DefConv-ReLU for processing, the input edge area is output and input into BatchNorm-2 x 2DefConv-SigMiod, an attention matrix is generated, the relation of the pixel points of the edge area is analyzed according to the attention value of each pixel point in the attention matrix, specifically, the attention values of the edge pixel points from the area A to the area B are compared, whether a gap larger than a preset threshold value exists or not is judged, and accordingly the change relation is determined. If the relation is abrupt, the gray level between the two areas is clear, the gray level does not need to be increased, and if the relation is gradual, the gray level needs to be additionally increased.
221. Determining frequency distribution data of each gray level for the acquired image of the display screen;
222. determining the total number of pixels of the acquired image of the display screen;
223. Calculating a histogram mean value of the acquired image of the display screen according to the number of gray levels, the frequency distribution data of each gray level and the total number of pixels;
The terminal determines the frequency distribution data of each gray level for the display screen collected image, then determines the total number of pixels of the display screen collected image, namely determines the accurate number of pixel points according to the gray levels, and finally calculates the histogram mean value of the display screen collected image according to the number of gray levels, the frequency distribution data of each gray level and the total number of pixels. The calculation method is already described in step 105 in embodiment 1, and will not be described here.
224. Performing standard analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen;
225. If the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time;
226. If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
Steps 224 to 226 in this embodiment are similar to steps 106 to 108 in the previous embodiment, and are not repeated here.
In this embodiment, the maximum gray-scale image is input to the calibration display screen for display, and the camera is used to collect the first calibration image of the calibration display screen. And calculating the brightness average value of the central area of the display screen according to the first image data of the first calibration image. An upper gray level limit and a lower gray level limit are set. Shooting the calibration display screen through the camera, and adjusting the exposure time of the camera in the shooting process to generate a third calibration image. When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level upper limit, determining the current exposure time as the first exposure time. When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level lower limit, determining the current exposure time as the second exposure time, wherein the first exposure time and the second exposure time form an exposure time range. The exposure time acquisition interval is determined from the exposure time range. Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring images by using a camera according to the exposure time acquisition interval to generate a second calibration image.
And calculating the gray average value of each second calibration image in the central area according to the second image data of the second calibration image. Fitting is carried out according to the exposure time of the camera, the brightness average value of the central area of the display screen and the gray average value of the second calibration image in the central area, and an exposure time model of the camera under the current working condition is generated.
And acquiring a plurality of pictures to be acquired, setting actual brightness for each picture to be acquired, and setting target gray scale of the acquired image of the display screen corresponding to the picture to be acquired. The method comprises the steps of inputting actual brightness and target gray scale into an exposure time model generated by a camera, and calculating to obtain the initial exposure time of each picture to be acquired, wherein the exposure time model is an initial exposure time calculation model generated by calibrating the brightness, the gray scale and the exposure time of the camera under the current working condition. The calculated initial exposure time is used for adjusting the camera, the corresponding picture to be acquired is input into the display screen to be detected, and the initial exposure time is not necessarily the optimal exposure time but is relatively close to the optimal exposure time. And acquiring images of the display screen to be tested by using a camera, and generating display screen acquired images.
And acquiring gray value data of each pixel point in the acquired image of the display screen. And carrying out regional pixel attention calculation for the pixel points of the acquired image of the display screen according to the gray value data, and generating regional attention data. And dividing the attention areas with different gray levels on the acquired image of the display screen according to the regional attention data. Generating an attention matrix for pixel points in the attention area according to the gray value data, and generating the area attention matrix. And dividing the pixel points in the attention area into different gray levels according to the area attention matrix. The number of gray levels of the two divisions is determined.
Frequency distribution data for each gray level is determined for the display screen acquisition image. The total number of pixels of the display screen captured image is determined. And calculating the histogram mean value of the acquired image of the display screen according to the number of gray levels, the frequency distribution data of each gray level and the total number of pixels.
And carrying out standard reaching analysis on the mean value of the histogram according to the target gray level corresponding to the acquired image of the display screen. If the average value of the histogram does not reach the standard, correcting the initial exposure time according to the target gray level and the average value of the histogram, and then re-acquiring, analyzing the histogram and analyzing the standard by using the initial exposure time. If the mean value of the histogram meets the standard, determining that the gray level of the acquired image of the display screen corresponding to the current picture to be acquired is qualified, and switching to the next picture to be acquired for analysis until all the pictures to be acquired are processed.
The method comprises the steps of calibrating an industrial-level camera used in a Demura process in advance, establishing a mathematical model between brightness, gray scale and exposure time, and then calculating the initial exposure time of a gray scale picture to be shot according to the exposure time model, the set brightness of a required gray scale picture (picture to be acquired) and the target gray scale of a display screen acquired image corresponding to the picture to be acquired. And adjusting the camera by using the calculated initial exposure time, acquiring a picture to be detected displayed on the display screen by the camera, carrying out gray level histogram analysis on the acquired display screen acquired image, judging whether the gray level on the display screen acquired image is qualified or not, further determining whether the exposure time is in conformity or not, and if the gray level is not qualified, further correcting and adjusting the exposure time by using the target gray level and the histogram mean value of the display screen acquired image, thereby realizing quick automatic exposure of the camera in the process of the display screen Demura. According to the method, manual adjustment is not needed, and the initial exposure time is corrected in an auxiliary mode through histogram analysis, gray level and histogram mean value, so that the exposure time adjustment times are greatly reduced, the iteration time is reduced, and the operation efficiency is improved.
Secondly, carrying out regional pixel attention calculation on the acquired images of the display screens and carrying out attention moment array generation on edge pixel points between the attention regions, dividing different gray levels for each acquired image of the display screens, reducing calculation time and improving calculation accuracy of a histogram mean value.
Referring to fig. 5, the present application provides an embodiment of a rapid auto-exposure apparatus for a display screen Demura, which includes:
The first acquisition unit 501 is configured to input the maximum gray-scale image into the calibration display screen for display, and acquire a first calibration image of the calibration display screen through the camera;
a second calculating unit 502, configured to calculate a brightness average value of a central area of the display screen according to first image data of the first calibration image;
A setting unit 503 for setting an upper gray level limit and a lower gray level limit;
a second determining unit 504, configured to determine an exposure time range corresponding to the camera through an upper gray level limit and a lower gray level limit;
optionally, the second determining unit 504 includes:
Shooting the calibration display screen through a camera, and adjusting the exposure time of the camera in the shooting process to generate a third calibration image;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level upper limit, determining the current exposure time as the first exposure time;
When the gray level of the third calibration image shot by the camera is in the gray level range determined by the gray level lower limit, determining the current exposure time as the second exposure time, wherein the first exposure time and the second exposure time form an exposure time range.
A second acquisition unit 505, configured to acquire at least two second calibration images within an exposure time range using a camera;
optionally, the second acquisition unit 505 includes:
determining an exposure time acquisition interval according to the exposure time range;
Inputting the maximum gray-scale picture into a calibration display screen for display, and acquiring images by using a camera according to the exposure time acquisition interval to generate a second calibration image.
A third calculating unit 506, configured to calculate a gray average value of each second calibration image in the central area according to the second image data of the second calibration image;
the third generating unit 507 is configured to fit according to the exposure time of the camera, the brightness average value of the central area of the display screen, and the gray average value of the second calibration image in the central area, and generate an exposure time model of the camera under the current working condition;
The acquiring unit 508 is configured to acquire a plurality of frames to be acquired, set actual brightness for each frame to be acquired, and set a target gray level of a display screen acquisition image corresponding to the frame to be acquired;
The first calculation unit 509 is configured to input the actual brightness and the target gray scale into an exposure time model, and calculate to obtain an initial exposure time of each frame to be acquired, where the exposure time model is an initial exposure time calculation model generated after the camera calibrates the brightness, the gray scale and the exposure time under the current working condition;
the adjusting unit 510 is configured to adjust the camera by using the calculated initial exposure time, and input a corresponding frame to be acquired into the display screen to be detected;
A first generating unit 511, configured to perform image acquisition on a display screen to be tested using a camera, and generate a display screen acquisition image;
A second generating unit 512, configured to perform histogram analysis on the acquired image of the display screen, and generate a histogram mean according to the result of the histogram analysis;
optionally, the second generating unit 512 includes:
a first determining module 5121, configured to divide gray levels for the acquired image of the display screen and determine the number of gray levels;
optionally, the first determining module 5121 includes:
Acquiring gray value data of each pixel point in an acquired image of a display screen;
performing regional pixel attention calculation for pixel points of the acquired image of the display screen according to the gray value data to generate regional attention data;
Dividing attention areas with different gray levels on the acquired images of the display screen according to the regional attention data;
Generating an attention matrix for edge pixel points among different attention areas according to the gray value data, and generating an area attention matrix;
Dividing different gray levels of pixel points in the attention area according to the area attention matrix;
the number of gray levels of the two divisions is determined.
A second determining module 5122, configured to determine frequency distribution data of each gray level for the acquired image of the display screen;
a third determining module 5123, configured to determine a total number of pixels of the image acquired by the display screen;
A calculating module 5124, configured to calculate a histogram mean of the display screen captured image according to the number of gray levels, the frequency distribution data of each gray level, and the total number of pixels.
The analysis unit 513 is configured to perform standard reaching analysis on the histogram mean according to the target gray level corresponding to the acquired image on the display screen;
A correction unit 514, configured to correct the initial exposure time according to the target gray level and the histogram mean value if the histogram mean value does not reach the standard, and re-perform acquisition, histogram analysis and standard analysis by using the initial exposure time;
The first determining unit 515 is configured to determine that the gray level of the acquired image of the display screen corresponding to the current frame to be acquired is qualified if the mean value of the histograms is within the preset range, and switch to the next frame to be acquired for analysis until all frames to be acquired are processed.
Referring to fig. 6, the present application provides an electronic device, including:
a processor 601, a memory 602, an input-output unit 603, and a bus 604.
The processor 601 is connected to a memory 602, an input-output unit 603, and a bus 604.
The memory 602 holds a program that the processor 601 invokes to execute the quick auto-exposure method as in fig. 1, 2, and 3 and 4.
The present application provides a computer-readable storage medium having a program stored thereon, which when executed on a computer performs a rapid auto-exposure method as in fig. 1,2 and 3 and 4.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function 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 with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
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 on 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.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
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 technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random-access memory (RAM, random access memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
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