Method and system for improving the picture clarity of LED grille screen based on machine vision

Abstract

The present invention relates to the field of grille screen technology, and is a method and system for improving the picture clarity of an LED grille screen based on machine vision, comprising: obtaining the crowd viewing density of the visual space sub-area, setting a machine vision image acquisition site set in the visual space sub-area according to the crowd viewing density, capturing a test display image of the LED grille screen to be tested according to the machine vision image acquisition site set, obtaining multiple groups of test display image sets, performing clarity assessment on each test display image, obtaining multiple groups of picture clarity sets, calculating the clarity mean of each group of picture clarity sets, obtaining a clarity mean set, calculating the picture display effect value of the LED grille screen to be tested, obtaining a picture display effect value set, identifying the grille point spacing corresponding to the maximum picture display effect value, and performing LED grille screen picture display according to the grille point spacing. The present invention can improve the picture clarity of the LED grille screen.

Description

Technical Field

[0001] The present invention relates to the technical field of grille screens, and in particular to a method and system for improving the picture clarity of an LED grille screen based on machine vision. Background Art

[0002] With the rapid development of LED display technology, LED grille screens have been widely used in outdoor advertising, stage performances, sports stadiums and other fields due to their advantages such as high brightness, high contrast and long life.

[0003] Since LED grille screens are usually made up of multiple LED modules, the brightness difference and gap feeling at the joints become important factors affecting the picture clarity, which leads to the low picture clarity of LED grille screens. Existing methods for improving the picture clarity of LED grille screens mainly rely on hardware performance improvements and traditional image processing algorithms. These methods do not adjust the distance between the LED grille screen's lamp beads in combination with complex and changeable application environments, resulting in limited improvement effects on the picture clarity of LED grille screens. Summary of the invention

[0004] The present invention provides a method and system for improving the picture clarity of an LED grille screen based on machine vision, the main purpose of which is to improve the picture clarity of the LED grille screen.

[0005] To achieve the above purpose, the present invention provides a method for improving the picture clarity of an LED grille screen based on machine vision, comprising:

[0006] Receiving an LED spatial display surface, and determining a visible spatial area of ​​the LED spatial display surface according to a preset viewing angle;

[0007] Acquire a viewing area type set, and divide the visible space area into regions according to the viewing area type set to obtain a visible space sub-region set;

[0008] Extracting visual space sub-regions in sequence from the visual space sub-region set, and obtaining the crowd viewing density of the visual space sub-regions;

[0009] According to the crowd viewing density, a machine vision image capturing point is set in the visible space sub-area to obtain a machine vision image capturing point set;

[0010] Constructing a set of LED grid screens to be tested according to a preset grid point spacing sequence, and sequentially extracting LED grid screens to be tested from the set of LED grid screens to be tested;

[0011] Capturing the test display image of the LED grille screen to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-area;

[0012] Performing clarity evaluation on each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets, and calculating a clarity mean of each picture clarity set to obtain a clarity mean value set;

[0013] According to the preset picture display effect formula, the picture display effect value of the LED grille screen to be tested is calculated using the clarity mean value set to obtain a picture display effect value set, wherein the picture display effect formula is as follows:

[0014] ,

[0015] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type;

[0016] The maximum picture display effect value is extracted from the picture display effect value set, the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grid screen picture is displayed according to the grid point spacing, thereby completing the picture clarity improvement of the LED grid screen based on machine vision.

[0017] Optionally, determining the visible space area of ​​the LED spatial display surface according to a preset visible angle includes:

[0018] Extracting spatial display surface edges in the LED spatial display surface in sequence, wherein the spatial display surface edges refer to the edges of the LED spatial display surface;

[0019] According to the visual angle, a visual boundary surface of the LED spatial display surface is formed through the spatial display surface, wherein the sum of the angle between the visual boundary surface and the LED spatial display surface and the visual angle is equal to 180 degrees;

[0020] Gather the visible boundary surfaces of the edges of each spatial display surface to obtain a visible boundary surface set;

[0021] Obtain a visible space area enclosed by the LED spatial display surface and the visible boundary surface set.

[0022] Optionally, dividing the visible space area according to the viewing area type set to obtain a visible space sub-area set includes:

[0023] Extracting viewing area types in the viewing area type set in sequence, identifying area boundary lines corresponding to the viewing area types in the visual space area, and obtaining an area boundary line set, wherein the viewing area type set includes: a motor vehicle area, a non-motor vehicle area, a traffic light waiting area, a walking area, and a leisure area;

[0024] The visible space region is divided into regions using the region boundary line set to obtain a visible space sub-region set.

[0025] Optionally, obtaining the crowd viewing density of the visual space sub-area includes:

[0026] Performing personnel entry monitoring on the sub-area of ​​the visible space according to a preset monitoring period and monitoring interval to obtain a number set of personnel entering the area;

[0027] The area of ​​the visible space sub-area is obtained, and the crowd viewing density is calculated according to the area of ​​the area and the number of people entering the area using the following formula:

[0028] ,

[0029] in, Indicates the viewing density of people. Indicates the number of people entering the first area in the number of people entering the area set. represents the number of people entering the jth area in the number of people entering the area set, Indicates the area of ​​a region.

[0030] Optionally, setting a machine vision image capturing site in the visible space sub-area according to the crowd viewing density to obtain a machine vision image capturing site set includes:

[0031] According to the viewing density of the flow of people, the number of ingestion sites is calculated using the following formula:

[0032] ,

[0033] in, represents the number of uptake sites, Indicates the floor symbol, Indicates the conversion ratio of crowd density;

[0034] According to the number of acquisition sites, the machine vision image acquisition sites are evenly arranged in the visible space sub-area to obtain a set of machine vision image acquisition sites.

[0035] Optionally, the performing clarity assessment on each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets includes:

[0036] Sequentially extracting test display images from the plurality of test display image sets, and intercepting LED image blocks from the test display images;

[0037] Dividing the LED image block into blocks to obtain an LED image sub-block set;

[0038] The LED image sub-blocks are sequentially extracted from the LED image sub-block set, and the brightness characteristic factor of the LED image sub-block is calculated using the following formula:

[0039] ,

[0040] in, Indicates The brightness characteristic factor of each LED image sub-block, lg represents the logarithmic function with base 10, and max() represents the maximum value sign. Indicates The brightness value of the first pixel in the LED image sub-block, Indicates The brightness value of the second pixel in the LED image sub-block, Indicates The brightness value of the nth pixel in the LED image sub-block, Indicates the number of pixels in the LED image block. Indicates the sequence number of the pixel in the LED image block. Indicates the first The brightness value of each pixel;

[0041] The lateral gradient value of each pixel in the LED image block is calculated using the following formula:

[0042] ,

[0043] in, Represents pixel The lateral gradient value, represents the absolute value symbol, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of

[0044] The longitudinal gradient value of each pixel in the LED image block is calculated using the following formula:

[0045] ,

[0046] in, Represents pixel The longitudinal gradient value, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of

[0047] According to the transverse gradient value and the longitudinal gradient value, a pre-constructed gradient formula is used to calculate the gradient value of each pixel in the LED image block;

[0048] According to the gradient value of each pixel point, a texture detail characteristic factor of the LED image sub-block is calculated using a pre-constructed texture detail formula;

[0049] Calculating the picture clarity of the test display image using a pre-constructed picture clarity formula according to the brightness characteristic factor and the texture detail characteristic factor;

[0050] The picture clarity of each test display image in each visual space sub-area is collected to obtain multiple groups of picture clarity sets.

[0051] Optionally, the texture detail formula is as follows:

[0052] ,

[0053] in, Indicates Texture detail feature factor of each LED image sub-block, Indicates The gradient value of the first pixel in the LED image sub-block, Indicates The gradient value of the second pixel in the LED image sub-block, Indicates The gradient value of the nth pixel in the LED image sub-block, Indicates the first The gradient value of a pixel.

[0054] Optionally, the picture clarity formula is as follows:

[0055] ,

[0056] in, Indicates the picture clarity of the test display image. Indicates the number of LED image sub-blocks in the LED image block.

[0057] Optionally, the gradient formula is as follows:

[0058] ,

[0059] in, Represents the pixel point in the LED image block The gradient value of .

[0060] To achieve the above purpose, the present invention also provides a system for improving the picture clarity of an LED grille screen based on machine vision, comprising:

[0061] A visible space area division module is used to receive an LED space display surface, determine a visible space area of ​​the LED space display surface according to a preset visual angle; obtain a viewing area type set, and divide the visible space area according to the viewing area type set to obtain a visible space sub-area set;

[0062] A clarity mean value set calculation module is used to sequentially extract visual space sub-regions from the visual space sub-region set to obtain the crowd viewing density of the visual space sub-region; set machine vision image acquisition sites in the visual space sub-region according to the crowd viewing density to obtain a machine vision image acquisition site set; construct a set of LED grille screens to be tested according to a preset grille point spacing sequence, and sequentially extract the LED grille screens to be tested from the set of LED grille screens to be tested; capture the test display images of the LED grille screens to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-region; perform clarity assessment on each test display image in the multiple groups of test display image sets to obtain multiple groups of picture clarity sets, and calculate the clarity mean of each group of picture clarity sets to obtain a clarity mean set;

[0063] The picture display effect value set calculation module is used to calculate the picture display effect value of the LED grille screen to be tested using the clarity mean value set according to a preset picture display effect formula to obtain a picture display effect value set, wherein the picture display effect formula is as follows:

[0064] ,

[0065] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type;

[0066] The LED grille screen picture display module is used to extract the maximum picture display effect value from the picture display effect value set, identify the grille point spacing corresponding to the maximum picture display effect value, and display the LED grille screen picture according to the grille point spacing.

[0067] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0068] A memory storing at least one instruction; and a processor executing the instructions stored in the memory to implement the above-mentioned method for improving the picture clarity of the LED grille screen based on machine vision.

[0069] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned method for improving the picture clarity of an LED grille screen based on machine vision.

[0070] In order to solve the problem described in the background technology, the present invention first needs to determine the visible space area, therefore, it is necessary to first receive the LED space display surface, determine the visible space area of ​​the LED space display surface according to the visible angle, then obtain a viewing area type set, divide the visible space area into regions according to the viewing area type set, and obtain a visible space sub-region set. In order to test the picture display effect of the LED grille screen to be tested in different visible space sub-regions, it is necessary to first obtain the crowd viewing density of the visible space sub-region, and then set the machine vision image acquisition site in the visible space sub-region according to the crowd viewing density to obtain a machine vision image acquisition site set. In order to test the optimal grille point spacing of the LED space display surface, it is necessary to construct a LED grille screen set to be tested according to a preset grille point spacing sequence, and extract the LED grilles to be tested in the LED grille screen set in sequence. At this time, the test display image of the LED grille screen to be tested can be captured according to the machine vision image capture site set to obtain multiple test display image sets, and then, the clarity of each test display image in the multiple test display image sets is evaluated to obtain multiple picture clarity sets, and finally, the clarity mean of each picture clarity set is calculated to obtain a clarity mean set. Since the display clarity effect of the LED grille screen to be tested needs to be calculated based on the clarity mean of each visual space sub-area, the picture display effect value of the LED grille screen to be tested can be calculated according to the preset picture display effect formula using the clarity mean set to obtain a picture display effect value set, and finally, the maximum picture display effect value is extracted from the picture display effect value set, and the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grille screen picture display can be performed according to the grid point spacing. Therefore, the present invention can improve the picture clarity of the LED grille screen. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A schematic flow chart of a method for improving the picture clarity of an LED grille screen based on machine vision provided by an embodiment of the present invention;

[0072] Figure 2 A functional module diagram of a system for improving the picture clarity of an LED grille screen based on machine vision provided by an embodiment of the present invention;

[0073] Figure 3 A schematic diagram of the structure of an electronic device for implementing the method for improving the picture clarity of an LED grille screen based on machine vision provided in one embodiment of the present invention.

[0074] Description of reference numerals:

[0075] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0076] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0077] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0078] The embodiment of the present application provides a method for improving the picture clarity of an LED grille screen based on machine vision. The execution subject of the method for improving the picture clarity of an LED grille screen based on machine vision includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for improving the picture clarity of an LED grille screen based on machine vision can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0079] Reference Figure 1 FIG. 1 is a flow chart of a method for improving the image clarity of an LED grille screen based on machine vision according to an embodiment of the present invention. In this embodiment, the method for improving the image clarity of an LED grille screen based on machine vision includes:

[0080] S1. Receive an LED spatial display surface, and determine a visible spatial area of ​​the LED spatial display surface according to a preset viewing angle.

[0081] It can be explained that the LED spatial display surface refers to the installation display area surface of the LED grille screen, and the viewing angle refers to the maximum and viewing standard viewing angle (obtuse angle) between the line of sight and the LED spatial display surface when viewing the LED grille screen in all directions, which can be 110 degrees.

[0082] Furthermore, the visible space area refers to the space area where the LED space display surface is viewed within the visible angle range in all directions.

[0083] In an embodiment of the present invention, determining the visible space area of ​​the LED spatial display surface according to a preset visible angle includes:

[0084] Extracting spatial display surface edges in the LED spatial display surface in sequence, wherein the spatial display surface edges refer to the edges of the LED spatial display surface;

[0085] According to the visual angle, a visual boundary surface of the LED spatial display surface is formed through the spatial display surface, wherein the sum of the angle between the visual boundary surface and the LED spatial display surface and the visual angle is equal to 180 degrees;

[0086] Gather the visible boundary surfaces of the edges of each spatial display surface to obtain a visible boundary surface set;

[0087] Obtain a visible space area enclosed by the LED spatial display surface and the visible boundary surface set.

[0088] It is understandable that the LED spatial display surface is generally a rectangle. When the LED spatial display surface is a rectangle, the spatial display surface edges are the edges of the rectangle. The visible boundary surface refers to the sight surface surrounded by the sight lines corresponding to the visual angle on the edge of the spatial display surface. For example, when the LED spatial display surface is a rectangle, there are four visible boundary surfaces, corresponding to the four edges of the rectangle.

[0089] S2. Obtain a viewing area type set, and divide the visible space area into regions according to the viewing area type set to obtain a visible space sub-region set.

[0090] It can be understood that the viewing area type set refers to a set of area types for viewing the LED spatial display surface. The visible space sub-area set refers to a set of viewing areas obtained after the visible space area is divided by the viewing area type set.

[0091] In the embodiment of the present invention, the step of dividing the visible space area according to the viewing area type set to obtain a visible space sub-area set includes:

[0092] Extracting viewing area types in the viewing area type set in sequence, identifying area boundary lines corresponding to the viewing area types in the visual space area, and obtaining an area boundary line set, wherein the viewing area type set includes: a motor vehicle area, a non-motor vehicle area, a traffic light waiting area, a walking area, and a leisure area;

[0093] The visible space region is divided into regions using the region boundary line set to obtain a visible space sub-region set.

[0094] It can be understood that the area boundary line refers to the boundary line of the visible space area. Since the LED grille screen is generally installed in a downtown area, the downtown area generally includes functional areas such as motor vehicle area, non-motor vehicle area, traffic light waiting area, pedestrian area, and leisure area. Therefore, the visible space area can be divided according to motor vehicle area, non-motor vehicle area, traffic light waiting area, pedestrian area, and leisure area.

[0095] S3. Extracting visual space sub-regions in sequence from the visual space sub-region set to obtain the crowd viewing density of the visual space sub-regions.

[0096] Furthermore, the crowd viewing density refers to the crowd density in the visual space sub-area. The greater the crowd viewing density, the more people are viewing the LED grille screen in the visual space sub-area.

[0097] In the embodiment of the present invention, obtaining the crowd viewing density of the visual space sub-area includes:

[0098] Performing personnel entry monitoring on the sub-area of ​​the visible space according to a preset monitoring period and monitoring interval to obtain a number set of personnel entering the area;

[0099] The area of ​​the visible space sub-area is obtained, and the crowd viewing density is calculated according to the area of ​​the area and the number of people entering the area using the following formula:

[0100] ,

[0101] in, Indicates the viewing density of people. Indicates the number of people entering the first area in the number of people entering the area set. represents the number of people entering the jth area in the number of people entering the area set, Indicates the area of ​​a region.

[0102] It can be explained that the monitoring period refers to the time period for monitoring the density of people viewing in the visual space sub-area, for example: 17:00-22:00. The monitoring interval refers to the length of the time interval for monitoring the number of people in the visual space sub-area during the monitoring period, for example: the monitoring interval can be 5 minutes, which means that the number of people in the visual space sub-area is counted every 5 minutes.

[0103] S4. Setting machine vision image acquisition sites in the visible space sub-area according to the crowd viewing density to obtain a machine vision image acquisition site set.

[0104] It is understandable that the machine vision image capturing site refers to the shooting position of an image capturing device (such as a CMOS or CCD camera). The machine vision image capturing site set refers to the set of machine vision image capturing sites within the visible space sub-area.

[0105] In the embodiment of the present invention, the step of setting a machine vision image acquisition point in the visible space sub-area according to the crowd viewing density to obtain a set of machine vision image acquisition points includes:

[0106] According to the viewing density of the flow of people, the number of ingestion sites is calculated using the following formula:

[0107] ,

[0108] in, represents the number of uptake sites, Indicates the floor symbol, Indicates the conversion ratio of crowd density;

[0109] According to the number of acquisition sites, the machine vision image acquisition sites are evenly arranged in the visible space sub-area to obtain a set of machine vision image acquisition sites.

[0110] It can be explained that the conversion ratio of the crowd density is a constant and can be set according to the actual situation, for example: 0.01. The uniform arrangement refers to setting the shooting positions of the image capture device at equal intervals in the spatial sub-area. The number of capture positions refers to the number of machine vision image capture positions in the machine vision image capture position set.

[0111] S5. Construct a set of LED grid screens to be tested according to a preset grid point spacing sequence, and sequentially extract the LED grid screens to be tested from the set of LED grid screens to be tested.

[0112] It is understandable that the grid point spacing sequence refers to the LED grid screen lamp bead spacing sequence, for example: 0.2cm, 0.4cm, 0.6cm, 0.8cm, 1cm, etc. The LED grid screen set to be tested refers to a set of grid screens with different grid point spacings waiting for picture clarity testing.

[0113] S6. Capturing the test display image of the LED grille screen to be tested according to the machine vision image capturing position set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a sub-area of ​​the visible space.

[0114] It is understandable that the test display image refers to an image of the LED grid screen display screen to be tested taken at the machine vision image capture site. The multiple test display image sets refer to a collection of test display images taken at each machine vision image capture site in each visual space sub-area.

[0115] S7. Evaluate the clarity of each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets, and calculate the clarity mean of each picture clarity set to obtain a clarity mean set.

[0116] It can be understood that the picture definition set refers to the set of picture definitions of the LED spatial display surface in each test display image in the test display image set. The definition mean value refers to the average value of the picture definition set.

[0117] In the embodiment of the present invention, the step of evaluating the clarity of each test display image in the plurality of test display image sets to obtain a plurality of image clarity sets includes:

[0118] Sequentially extracting test display images from the plurality of test display image sets, and intercepting LED image blocks from the test display images;

[0119] Dividing the LED image block into blocks to obtain an LED image sub-block set;

[0120] The LED image sub-blocks are sequentially extracted from the LED image sub-block set, and the brightness characteristic factor of the LED image sub-block is calculated using the following formula:

[0121] ,

[0122] in, Indicates The brightness characteristic factor of each LED image sub-block, lg represents the logarithmic function with base 10, and max() represents the maximum value sign. Indicates The brightness value of the first pixel in the LED image sub-block, Indicates The brightness value of the second pixel in the LED image sub-block, Indicates The brightness value of the nth pixel in the LED image sub-block, Indicates the number of pixels in the LED image block. Indicates the sequence number of the pixel in the LED image block. Indicates the first The brightness value of each pixel;

[0123] The lateral gradient value of each pixel in the LED image block is calculated using the following formula:

[0124] ,

[0125] in, Represents pixel The lateral gradient value, represents the absolute value symbol, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of

[0126] The longitudinal gradient value of each pixel in the LED image block is calculated using the following formula:

[0127] ,

[0128] in, Represents pixel The longitudinal gradient value, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of

[0129] According to the transverse gradient value and the longitudinal gradient value, a pre-constructed gradient formula is used to calculate the gradient value of each pixel in the LED image block;

[0130] According to the gradient value of each pixel point, a texture detail characteristic factor of the LED image sub-block is calculated using a pre-constructed texture detail formula;

[0131] Calculating the picture clarity of the test display image using a pre-constructed picture clarity formula according to the brightness characteristic factor and the texture detail characteristic factor;

[0132] The picture clarity of each test display image in each visual space sub-area is collected to obtain multiple groups of picture clarity sets.

[0133] Furthermore, the LED image block refers to the block corresponding to the image displayed on the LED spatial display surface in the test display image. The LED image sub-block set refers to the set of LED image sub-blocks after the LED image block is divided. For example, when the LED image block is a square with a side length of 10 cm and the side length of the division is 5 cm, the LED image sub-block can be a square area with a side length of 5 cm.

[0134] It is understandable that since the test display image is an image including an LED display screen taken by an image acquisition device, and the embodiment of the present invention only needs to evaluate the clarity of the LED display screen, it is necessary to capture the LED image block in the test display image to realize the clarity calculation of the LED image block.

[0135] Furthermore, when the LED image block takes the upper left corner vertex as the coordinate origin, the right is the positive direction of the x-axis, and the downward is the positive direction of the y-axis, then the pixel point Indicates that the horizontal coordinate in the LED image block is , the vertical axis is Therefore, the pixel Represents pixel The pixel point adjacent to the upper left corner of Represents pixel The pixel point adjacent to the left of Represents pixel The pixel point adjacent to the lower left corner of Represents pixel The pixel point adjacent to the upper right corner of Represents pixel The pixel point adjacent to the right of Represents pixel The pixel adjacent to the lower right corner.

[0136] It can be understood that the brightness characteristic factor refers to a parameter representing the brightness characteristics of the LED image sub-block, such as brightness uniformity and brightness stability. The horizontal gradient value refers to the horizontal grayscale gradient of the pixel point, and the vertical gradient value refers to the vertical grayscale gradient of the pixel point. The gradient value refers to the degree of grayscale difference between a pixel point and an adjacent pixel point. The texture detail characteristic factor refers to a characteristic parameter representing the clarity of the texture details of the LED image sub-block. The picture clarity refers to the clarity of the test display image. Each set of picture clarity sets corresponds to a set of picture clarity of each test display image in a sub-area of ​​the visual space.

[0137] In the embodiment of the present invention, the gradient formula is as follows:

[0138] ,

[0139] in, Represents the pixel point in the LED image block The gradient value of .

[0140] In the embodiment of the present invention, the texture detail formula is as follows:

[0141] ,

[0142] in, Indicates Texture detail feature factor of each LED image sub-block, Indicates The gradient value of the first pixel in the LED image sub-block, Indicates The gradient value of the second pixel in the LED image sub-block, Indicates The gradient value of the nth pixel in the LED image sub-block, Indicates the first The gradient value of a pixel.

[0143] In the embodiment of the present invention, the picture clarity formula is as follows:

[0144] ,

[0145] in, Indicates the picture clarity of the test display image. Indicates the number of LED image sub-blocks in the LED image block.

[0146] S8. According to a preset picture display effect formula, the picture display effect value of the LED grille screen to be tested is calculated using the clarity mean value set to obtain a picture display effect value set.

[0147] It can be understood that the picture display effect value refers to the picture display effect evaluation value of the LED grille screen to be tested. The picture display effect value set refers to the set of picture display effect values ​​of each LED grille screen to be tested.

[0148] In detail, the screen display effect formula is as follows:

[0149] ,

[0150] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, Type number representing the viewing area type.

[0151] It can be understood that the area type weight value is the calculated weight of each viewing area type. The larger the area type weight, the greater the importance of the corresponding viewing area type. Generally, the area with a greater viewing density of people has a larger area type weight value. For example, the area type weight value of the motor vehicle area is 0.1, the area type weight value of the non-motor vehicle area is 0.1, the area type weight value of the traffic light waiting area is 0.2, the area type weight value of the pedestrian area is 0.2, and the area type weight value of the leisure area is 0.4.

[0152] S9. Extract the maximum picture display effect value from the picture display effect value set, identify the grid point spacing corresponding to the maximum picture display effect value, display the LED grid screen according to the grid point spacing, and improve the picture clarity of the LED grid screen based on machine vision.

[0153] It is understandable that the maximum picture display effect value refers to the maximum picture display effect value in the picture display effect value set. In the embodiment of the present invention, the grid point spacing is the only factor affecting the picture clarity, so the grid point spacing corresponding to the maximum picture display effect value in the grid point spacing sequence can be identified, and then the LED grid screen is prepared according to the grid point spacing for picture display, so that the LED grid screen achieves the best picture clarity.

[0154] In order to solve the problem described in the background technology, the present invention first needs to determine the visible space area, therefore, it is necessary to first receive the LED space display surface, determine the visible space area of ​​the LED space display surface according to the visible angle, then obtain a viewing area type set, divide the visible space area into regions according to the viewing area type set, and obtain a visible space sub-region set. In order to test the picture display effect of the LED grille screen to be tested in different visible space sub-regions, it is necessary to first obtain the crowd viewing density of the visible space sub-region, and then set the machine vision image acquisition site in the visible space sub-region according to the crowd viewing density to obtain a machine vision image acquisition site set. In order to test the optimal grille point spacing of the LED space display surface, it is necessary to construct a LED grille screen set to be tested according to a preset grille point spacing sequence, and extract the LED grilles to be tested in the LED grille screen set in sequence. At this time, the test display image of the LED grille screen to be tested can be captured according to the machine vision image capture site set to obtain multiple test display image sets, and then, the clarity of each test display image in the multiple test display image sets is evaluated to obtain multiple picture clarity sets, and finally, the clarity mean of each picture clarity set is calculated to obtain a clarity mean set. Since the display clarity effect of the LED grille screen to be tested needs to be calculated based on the clarity mean of each visual space sub-area, the picture display effect value of the LED grille screen to be tested can be calculated according to the preset picture display effect formula using the clarity mean set to obtain a picture display effect value set, and finally, the maximum picture display effect value is extracted from the picture display effect value set, and the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grille screen picture display can be performed according to the grid point spacing. Therefore, the present invention can improve the picture clarity of the LED grille screen.

[0155] like Figure 2 , which is a functional module diagram of a system for improving the picture clarity of an LED grille screen based on machine vision provided by an embodiment of the present invention.

[0156] The system 100 for improving the picture clarity of an LED grille screen based on machine vision according to the present invention can be installed in an electronic device. According to the functions implemented, the system 100 for improving the picture clarity of an LED grille screen based on machine vision can include a visible space area division module 101, a clarity mean value set calculation module 102, a picture display effect value set calculation module 103, and an LED grille screen picture display module 104. The module according to the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0157] The visible space region division module 101 is used to receive an LED space display surface, determine the visible space region of the LED space display surface according to a preset visual angle; obtain a viewing area type set, and divide the visible space region according to the viewing area type set to obtain a visible space sub-region set;

[0158] The clarity mean value set calculation module 102 is used to sequentially extract the visual space sub-regions from the visual space sub-region set to obtain the crowd viewing density of the visual space sub-region; set the machine vision image acquisition site in the visual space sub-region according to the crowd viewing density to obtain the machine vision image acquisition site set; construct the LED grid screen set to be tested according to the preset grid point spacing sequence, and sequentially extract the LED grid screens to be tested from the LED grid screen set to be tested; capture the test display image of the LED grid screen to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-region; perform clarity assessment on each test display image in the multiple groups of test display image sets to obtain multiple groups of picture clarity sets, and calculate the clarity mean of each group of picture clarity sets to obtain a clarity mean set;

[0159] The picture display effect value set calculation module 103 is used to calculate the picture display effect value of the LED grille screen to be tested using the clarity mean value set according to a preset picture display effect formula to obtain a picture display effect value set, wherein the picture display effect formula is as follows:

[0160] ,

[0161] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type;

[0162] The LED grille screen image display module 104 is used to extract the maximum image display effect value from the image display effect value set, identify the grille point spacing corresponding to the maximum image display effect value, and perform LED grille screen image display according to the grille point spacing.

[0163] In detail, the modules in the system 100 for improving the picture clarity of LED grille screen based on machine vision in the embodiment of the present invention are used in the same manner as described above. Figure 1 The method of improving the picture clarity of the LED grille screen based on machine vision is the same technical means as described in the text and can produce the same technical effects, so I will not go into details here.

[0164] like Figure 3 , is a schematic diagram of the structure of an electronic device for implementing a method for improving the picture clarity of an LED grille screen based on machine vision provided by an embodiment of the present invention.

[0165] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a method program for improving the picture clarity of an LED grille screen based on machine vision.

[0166] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the program of the method for improving the picture clarity of the LED grille screen based on machine vision, but also can be used to temporarily store data that has been output or is to be output.

[0167] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (for example, a method program for improving the picture clarity of an LED grille screen based on machine vision, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0168] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0169] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0170] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0171] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0172] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0173] The program of the method for improving the picture clarity of the LED grille screen based on machine vision stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0174] Receiving an LED spatial display surface, and determining a visible spatial area of ​​the LED spatial display surface according to a preset viewing angle;

[0175] Acquire a viewing area type set, and divide the visible space area into regions according to the viewing area type set to obtain a visible space sub-region set;

[0176] Extracting visual space sub-regions in sequence from the visual space sub-region set, and obtaining the crowd viewing density of the visual space sub-regions;

[0177] According to the crowd viewing density, a machine vision image capturing point is set in the visible space sub-area to obtain a machine vision image capturing point set;

[0178] Constructing a set of LED grid screens to be tested according to a preset grid point spacing sequence, and sequentially extracting LED grid screens to be tested from the set of LED grid screens to be tested;

[0179] Capturing the test display image of the LED grille screen to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-area;

[0180] Performing clarity evaluation on each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets, and calculating a clarity mean of each picture clarity set to obtain a clarity mean value set;

[0181] According to the preset picture display effect formula, the picture display effect value of the LED grille screen to be tested is calculated using the clarity mean value set to obtain a picture display effect value set, wherein the picture display effect formula is as follows:

[0182] ,

[0183] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type;

[0184] The maximum picture display effect value is extracted from the picture display effect value set, the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grid screen picture is displayed according to the grid point spacing, thereby completing the picture clarity improvement of the LED grid screen based on machine vision.

[0185] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0186] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0187] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0188] Receiving an LED spatial display surface, and determining a visible spatial area of ​​the LED spatial display surface according to a preset viewing angle;

[0189] Acquire a viewing area type set, and divide the visible space area into regions according to the viewing area type set to obtain a visible space sub-region set;

[0190] Extracting visual space sub-regions in sequence from the visual space sub-region set, and obtaining the crowd viewing density of the visual space sub-regions;

[0191] According to the crowd viewing density, a machine vision image capturing point is set in the visible space sub-area to obtain a machine vision image capturing point set;

[0192] Constructing a set of LED grid screens to be tested according to a preset grid point spacing sequence, and sequentially extracting LED grid screens to be tested from the set of LED grid screens to be tested;

[0193] Capturing the test display image of the LED grille screen to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-area;

[0194] Performing clarity evaluation on each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets, and calculating a clarity mean of each picture clarity set to obtain a clarity mean value set;

[0195] According to the preset picture display effect formula, the picture display effect value of the LED grille screen to be tested is calculated using the clarity mean value set to obtain a picture display effect value set, wherein the picture display effect formula is as follows:

[0196] ,

[0197] in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type;

[0198] The maximum picture display effect value is extracted from the picture display effect value set, the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grid screen picture is displayed according to the grid point spacing, thereby completing the picture clarity improvement of the LED grid screen based on machine vision.

[0199] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0200] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0201] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0202] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0203] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for improving the picture clarity of an LED grille screen based on machine vision, characterized in that: The method comprises: Receiving an LED spatial display surface, and determining a visible spatial area of ​​the LED spatial display surface according to a preset viewing angle; Acquire a viewing area type set, and divide the visible space area into regions according to the viewing area type set to obtain a visible space sub-region set; Extracting visual space sub-regions in sequence from the visual space sub-region set, and obtaining the crowd viewing density of the visual space sub-region; According to the crowd viewing density, a machine vision image capturing point is set in the visible space sub-area to obtain a machine vision image capturing point set; Constructing a set of LED grid screens to be tested according to a preset grid point spacing sequence, and sequentially extracting LED grid screens to be tested from the set of LED grid screens to be tested; Capturing the test display image of the LED grille screen to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-area; Performing clarity evaluation on each test display image in the plurality of test display image sets to obtain a plurality of picture clarity sets, and calculating a clarity mean of each picture clarity set to obtain a clarity mean value set; According to the preset picture display effect formula, the picture display effect value of the LED grille screen to be tested is calculated using the clarity mean value set to obtain a picture display effect value set, wherein the picture display effect formula is as follows: ， in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type; The maximum picture display effect value is extracted from the picture display effect value set, the grid point spacing corresponding to the maximum picture display effect value is identified, and the LED grid screen picture is displayed according to the grid point spacing, thereby completing the picture clarity improvement of the LED grid screen based on machine vision.

2. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 1, characterized in that: Determining the visible space area of ​​the LED spatial display surface according to a preset visible angle includes: Extracting spatial display surface edges in the LED spatial display surface in sequence, wherein the spatial display surface edges refer to the edges of the LED spatial display surface; According to the visual angle, a visual boundary surface of the LED spatial display surface is formed through the spatial display surface, wherein the sum of the angle between the visual boundary surface and the LED spatial display surface and the visual angle is equal to 180 degrees; Gather the visible boundary surfaces of the edges of each spatial display surface to obtain a visible boundary surface set; Obtain a visible space area enclosed by the LED spatial display surface and the visible boundary surface set.

3. The method for improving the picture clarity of the LED grille screen based on machine vision as claimed in claim 2, characterized in that: The step of dividing the visible space area according to the viewing area type set to obtain a visible space sub-area set includes: Extracting viewing area types in the viewing area type set in sequence, identifying area boundary lines corresponding to the viewing area types in the visual space area, and obtaining an area boundary line set, wherein the viewing area type set includes: a motor vehicle area, a non-motor vehicle area, a traffic light waiting area, a walking area, and a leisure area; The visible space region is divided into regions using the region boundary line set to obtain a visible space sub-region set.

4. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 1, characterized in that: The obtaining of the crowd viewing density of the visual space sub-area includes: Performing personnel entry monitoring on the sub-area of ​​the visible space according to a preset monitoring period and monitoring interval to obtain a number set of personnel entering the area; The area of ​​the visible space sub-area is obtained, and the crowd viewing density is calculated according to the area of ​​the area and the number of people entering the area using the following formula: ， in, Indicates the viewing density of people. Indicates the number of people entering the first area in the number of people entering the area set. represents the number of people entering the jth area in the number of people entering the area set, Indicates the area of ​​a region.

5. The method for improving the picture clarity of LED grille screen based on machine vision as claimed in claim 4, characterized in that: The setting of machine vision image acquisition sites in the visible space sub-area according to the crowd viewing density to obtain a set of machine vision image acquisition sites includes: According to the viewing density of the flow of people, the number of ingestion sites is calculated using the following formula: ， in, represents the number of uptake sites, Indicates the floor symbol, Indicates the conversion ratio of crowd density; According to the number of acquisition sites, the machine vision image acquisition sites are evenly arranged in the visible space sub-region to obtain a set of machine vision image acquisition sites.

6. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 1, characterized in that: The step of evaluating the clarity of each test display image in the plurality of test display image sets to obtain a plurality of image clarity sets includes: Sequentially extracting test display images from the plurality of test display image sets, and intercepting LED image blocks from the test display images; Dividing the LED image block into blocks to obtain an LED image sub-block set; The LED image sub-blocks are sequentially extracted from the LED image sub-block set, and the brightness characteristic factor of the LED image sub-block is calculated using the following formula: ， in, Indicates The brightness characteristic factor of each LED image sub-block, lg represents the logarithmic function with base 10, and max() represents the maximum value sign. Indicates The brightness value of the first pixel in the LED image sub-block, Indicates The brightness value of the second pixel in the LED image sub-block, Indicates The brightness value of the nth pixel in the LED image sub-block, Indicates the number of pixels in the LED image block. Indicates the sequence number of the pixel in the LED image block. Indicates the first The brightness value of each pixel; The lateral gradient value of each pixel in the LED image block is calculated using the following formula: ， in, Represents pixel The lateral gradient value, represents the absolute value symbol, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of The longitudinal gradient value of each pixel in the LED image block is calculated using the following formula: ， in, Represents pixel The longitudinal gradient value, Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel The gray value of Represents pixel Gray value of According to the transverse gradient value and the longitudinal gradient value, a pre-constructed gradient formula is used to calculate the gradient value of each pixel in the LED image block; According to the gradient value of each pixel point, a texture detail characteristic factor of the LED image sub-block is calculated using a pre-constructed texture detail formula; Calculating the picture clarity of the test display image using a pre-constructed picture clarity formula according to the brightness characteristic factor and the texture detail characteristic factor; The picture clarity of each test display image in each visual space sub-area is collected to obtain multiple groups of picture clarity sets.

7. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 6, characterized in that: The texture detail formula is as follows: ， in, Indicates Texture detail feature factor of each LED image sub-block, Indicates The gradient value of the first pixel in the LED image sub-block, Indicates The gradient value of the second pixel in the LED image sub-block, Indicates The gradient value of the nth pixel in the LED image sub-block, Indicates the first The gradient value of a pixel.

8. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 7, characterized in that: The picture clarity formula is as follows: ， in, Indicates the picture clarity of the test display image. Indicates the number of LED image sub-blocks in the LED image block.

9. The method for improving the picture clarity of an LED grille screen based on machine vision as claimed in claim 7, characterized in that: The gradient formula is as follows: ， in, Represents the pixel point in the LED image block The gradient value of .

10. A system for improving the picture clarity of LED grille screen based on machine vision, characterized in that: The system comprises: A visible space area division module is used to receive an LED space display surface, determine a visible space area of ​​the LED space display surface according to a preset visual angle; obtain a viewing area type set, and divide the visible space area according to the viewing area type set to obtain a visible space sub-area set; A clarity mean value set calculation module is used to sequentially extract visual space sub-regions from the visual space sub-region set to obtain the crowd viewing density of the visual space sub-region; set machine vision image acquisition sites in the visual space sub-region according to the crowd viewing density to obtain a machine vision image acquisition site set; construct a set of LED grille screens to be tested according to a preset grille point spacing sequence, and sequentially extract the LED grille screens to be tested from the set of LED grille screens to be tested; capture the test display images of the LED grille screens to be tested according to the machine vision image acquisition site set to obtain multiple groups of test display image sets, wherein each group of test display image sets corresponds to a visual space sub-region; perform clarity assessment on each test display image in the multiple groups of test display image sets to obtain multiple groups of picture clarity sets, and calculate the clarity mean of each group of picture clarity sets to obtain a clarity mean set; The picture display effect value set calculation module is used to calculate the picture display effect value of the LED grille screen to be tested using the clarity mean value set according to a preset picture display effect formula to obtain a picture display effect value set, wherein the picture display effect formula is as follows: ， in, Indicates the screen display effect value. represents the weight of the first area type, represents the mean value of the first group of picture clarity sets, represents the second area type weight, represents the mean value of the second group of picture clarity sets, Indicates Area type weight, Indicates The mean value of the clarity of the group picture clarity set, The type number indicating the viewing area type; The LED grille screen picture display module is used to extract the maximum picture display effect value from the picture display effect value set, identify the grille point spacing corresponding to the maximum picture display effect value, and display the LED grille screen picture according to the grille point spacing.

Images