CN-122023409-A - Intelligent testing method and system for brightness uniformity of curved screen

CN122023409ACN 122023409 ACN122023409 ACN 122023409ACN-122023409-A

Abstract

The application relates to the technical field of curved surface screen brightness detection, in particular to an intelligent testing method and system for the brightness uniformity of a curved surface screen, wherein the method comprises the steps of obtaining a full-bright screen image and a dark field image of the curved surface screen based on darkroom operation specifications, and carrying out brightness conversion on the full-bright screen image; the method comprises the steps of establishing an approximate perspective projection parabolic model, obtaining observation view angles in different directions on a curved surface corresponding to the approximate perspective projection parabolic model, establishing an observation view angle matrix, determining a brightness-angle response function based on a functional relation between view angles and brightness values in the observation view angle matrix to obtain intrinsic brightness values, determining screen brightness uniformity at each pixel point position based on differences of distribution of the intrinsic brightness values of each pixel point position and all pixel point positions, and obtaining a testing result of the brightness uniformity of a curved surface screen based on the screen brightness uniformity. The application aims to improve the accuracy of the brightness test result of the curved screen.

Inventors

JIANG QIAOQIAO
GUAN GANG
ZHAO YONG
LUO SHUANGQUAN

Assignees

深圳市米多智造科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The intelligent testing method for the brightness uniformity of the curved screen is characterized by comprising the following steps of: performing exposure photographing under a curved screen full-white field signal based on darkroom operation specifications to obtain a full-bright screen image, comparing the central brightness of the screen obtained by different brightness meters, and performing brightness conversion on the full-bright screen image by combining the darkfield image when the curved screen is not light; Based on the edge detection result of the full-bright screen image, an approximate perspective projection parabolic model is established, and on the corresponding curved surface of the approximate perspective projection parabolic model, observation view angles in different directions are obtained, and an observation view angle matrix is established; analyzing a function relation between a view angle and a brightness value in an observation view angle matrix, determining a brightness-angle response function, and compensating the brightness value obtained at each pixel point position to obtain an intrinsic brightness value; And determining the screen brightness uniformity at each pixel position based on the difference of the intrinsic brightness value distribution of each pixel position and all pixel positions, and obtaining a test result of the curved surface screen brightness uniformity based on the screen brightness uniformity.
2. The intelligent testing method for brightness uniformity of curved screen according to claim 1, wherein said brightness conversion of full-bright screen image is specifically as follows: The gray level difference of the full-bright screen image and the dark field image at each pixel position is obtained, and the gray level difference is subjected to forward fusion with the screen center brightness comparison result obtained by different brightness meters at each pixel position to obtain a first forward fusion result; the luminance value at each pixel location is determined by the ratio of the first forward fusion result to the second forward fusion result.
3. The intelligent testing method for brightness uniformity of curved screen according to claim 2, wherein the flat field correction coefficient obtaining process is as follows: And continuously acquiring N standard uniform light source images without any object, averaging pixel point values at the same position of all the images to acquire an average image, and taking the pixel value at each pixel position in the average image as a corresponding flat field correction coefficient.
4. The intelligent testing method for brightness uniformity of curved screen according to claim 1, wherein said establishing an approximate perspective projection parabolic model comprises the following specific formulas: In the formula, the total number of the components is calculated, As a parameter of the curvature of the web, Is the center abscissa of the image, C is the intercept, U represents the abscissa of the pixel location as a curved parabolic function.
5. The intelligent testing method for brightness uniformity of a curved screen according to claim 4, wherein said curvature parameter and said intercept are obtained by minimizing an error between a parabolic curve function and an edge detection result for a full bright screen image.
6. The intelligent testing method of brightness uniformity of a curved screen according to claim 1, wherein the observation view angle is specifically an included angle between a vector of an imaging brightness meter optical axis pointing to a screen center and a normal vector of a curved surface corresponding to an approximately perspective projection parabolic model at each pixel point position.
7. The intelligent testing method for brightness uniformity of a curved screen according to claim 1, wherein said intrinsic brightness value is specifically a ratio of a brightness value at each pixel position to a brightness-angle response function value corresponding to an observation angle at the corresponding position.
8. The intelligent testing method for brightness uniformity of curved screen according to claim 1, wherein said determining the brightness uniformity of the screen at each pixel position is specifically: Taking the average value of the intrinsic brightness values at all pixel point positions except the maximum intrinsic brightness value and the minimum intrinsic brightness value in the full-bright screen image as a global reference brightness value; And calculating the product of the global reference brightness value and a preset Weber score, and taking the ratio of the obtained difference to the product as the uniformity of the screen brightness at each pixel position.
9. The intelligent testing method for brightness uniformity of a curved screen according to claim 1, wherein the process of obtaining the testing result of brightness uniformity of the curved screen is specifically as follows: and counting the number of pixel points with the screen brightness uniformity larger than a first preset value at all pixel points of the whole curved surface screen, if the number of pixel points is smaller than a preset percentage and the maximum value of the screen brightness uniformity is smaller than a second preset value, judging that the curved surface screen brightness is uniform, otherwise, the curved surface screen brightness is nonuniform.
10. A curved screen brightness uniformity intelligent test system comprising a memory, a processor and a computer program stored in said memory and running on said processor, wherein said processor implements the steps of the method according to any one of claims 1-9 when said computer program is executed by said processor.

Description

Intelligent testing method and system for brightness uniformity of curved screen Technical Field The application relates to the technical field of brightness detection of curved screens, in particular to an intelligent testing method and system for brightness uniformity of a curved screen. Background The curved surface display structure is widely applied to the fields of high-end displays, vehicle-mounted cabins, mobile terminals and the like because the curved surface display structure accords with the physiological characteristics of human eyes and can provide immersive visual experience. At present, related standards such as GB/T38001.52-2024 and the like are released in China, and clear brightness uniformity is a key index for evaluating display quality, which directly influences application effects in professional fields such as image display, color design and the like. At present, the brightness uniformity testing technology is mainly divided into two major types, namely a point scanning type and an area array imaging type, in the point scanning type testing process, the axis of a probe is strictly vertical to a local tangent plane of a screen at a measuring point, the single-point measuring mode causes the defect that the point-by-point movement and the reading time are longer in the testing process, and the high-speed full-inspection requirement of a modern production line cannot be met, while the imaging type brightness meter measuring technology captures a brightness distribution image of the whole screen by utilizing an area array CCD (charge coupled device), and the imaging type brightness meter has the characteristics of large visual field, high speed and high resolution. However, in the practical application process, even if the screen emits light uniformly, the geometric bending of the curved screen causes the increase of the observation angle of view of the screen edge and the camera, so that the conventional test system is difficult to accurately distinguish, and misjudgment is caused. Disclosure of Invention In view of the foregoing, it is necessary to provide a method and a system for intelligently testing brightness uniformity of a curved screen, so as to solve the above problems. The application provides an intelligent testing method for brightness uniformity of a curved screen, which comprises the following steps: performing exposure photographing under a curved screen full-white field signal based on darkroom operation specifications to obtain a full-bright screen image, comparing the central brightness of the screen obtained by different brightness meters, and performing brightness conversion on the full-bright screen image by combining the darkfield image when the curved screen is not light; Based on the edge detection result of the full-bright screen image, an approximate perspective projection parabolic model is established, and on the corresponding curved surface of the approximate perspective projection parabolic model, observation view angles in different directions are obtained, and an observation view angle matrix is established; analyzing a function relation between a view angle and a brightness value in an observation view angle matrix, determining a brightness-angle response function, and compensating the brightness value obtained at each pixel point position to obtain an intrinsic brightness value; And determining the screen brightness uniformity at each pixel position based on the difference of the intrinsic brightness value distribution of each pixel position and all pixel positions, and obtaining a test result of the curved surface screen brightness uniformity based on the screen brightness uniformity. Preferably, the brightness conversion of the full-bright screen image is specifically: The gray level difference of the full-bright screen image and the dark field image at each pixel position is obtained, and the gray level difference is subjected to forward fusion with the screen center brightness comparison result obtained by different brightness meters at each pixel position to obtain a first forward fusion result; the luminance value at each pixel location is determined by the ratio of the first forward fusion result to the second forward fusion result. Preferably, the flat field correction coefficient is obtained by the following steps: And continuously acquiring N standard uniform light source images without any object, averaging the pixel point number values of all the images to acquire an average image, and taking the pixel value at each pixel position in the average image as a corresponding flat field correction coefficient. Preferably, the establishing an approximate perspective projection parabolic model comprises the following specific formulas: In the formula, the total number of the components is calculated, As a parameter of the curvature of the web,Is the center abscissa of the image, C is the intercept,U represents the abscissa of the pixel location as