A 3D animation graphics and image processing system based on AI artificial intelligence

Abstract

The present invention discloses a 3D animation graphics image processing system based on AI artificial intelligence, which specifically relates to the field of computer graphics, including a 3D image scene determination module, a 3D scene image information acquisition module, a data standardization processing module, a 3D image text processing module, a 3D image text comprehensive processing module, an image processing comprehensive judgment module, and an interactive feedback module. The present invention realizes comprehensive monitoring of the target area through precise area division, and covers key information of the three dimensions of picture quality, rendering effect and efficiency by collecting frame rate, QP value, number of grids and textures, pixel accuracy, error, rendering time, memory occupancy rate and image quality indicators (SSIM, PSNR), etc., and establishes a comprehensive mathematical model to comprehensively evaluate the comprehensive performance of the 3D animation graphics image processing system, thereby improving the work efficiency and quality of 3D animation graphics image processing.

Description

Technical Field

[0001] The present invention relates to the technical field of computer graphics, and more specifically, to a three-dimensional animation graphics image processing system based on AI artificial intelligence. Background Art

[0002] 3D animation graphics and image processing refers to the use of computer technology to produce animation effects and optimize graphics and images for 3D models. This process involves 3D modeling, material mapping, lighting settings, animation production, rendering output and other links, aiming to create realistic and vivid 3D animation effects.

[0003] With the rapid development of artificial intelligence technology, the application of 3D animation graphics and image processing systems in image processing, animation production and other fields is becoming more and more extensive. As an important tool for digital content creation, the intelligence level of 3D animation graphics and image processing systems directly affects the efficiency and quality of animation production. Therefore, 3D animation graphics and image processing systems based on AI artificial intelligence came into being, aiming to improve the intelligence level of 3D animation graphics and image production through artificial intelligence technology.

[0004] However, there are still some shortcomings in its actual use. For example, the data collected by the existing technology is too single, which makes it difficult to accurately judge the overall effect and performance of the 3D animation graphics and image processing system. In addition, the current monitoring of system performance is mainly judged by a single dimension such as frame rate, resolution, and number of grids, lacking comprehensive indicators. If monitoring is only carried out from a single dimension, ignoring the memory pressure caused by rendering, the smoothness of animation production, the image quality before and after processing, and the impact of processing effects, then the evaluation of the 3D animation graphics and image processing system may not be comprehensive enough, which in turn affects the final work quality and efficiency of the 3D animation graphics and image processing system. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a three-dimensional animation graphics image processing system based on AI artificial intelligence, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: a three-dimensional animation graphic image processing system based on AI artificial intelligence, including a system operation database, a system central processing module and a user information terminal, and also including a three-dimensional image scene determination module, a three-dimensional scene image information acquisition module, a data standardization processing module, a three-dimensional image text processing module, a three-dimensional image text comprehensive processing module, an image processing comprehensive judgment module and an interactive feedback module.

[0007] Preferably, the system operation database includes all data texts of the three-dimensional animation graphic image processing system, and collects the information text output by each module in real time. The system central processing module is used to centrally control the information text instructions output by each module, and the user information terminal is an information output device for receiving the three-dimensional animation graphic image processing system;

[0008] Preferably, the three-dimensional image scene determination module: the three-dimensional image scene determination module: screens feature text data based on accurate three-dimensional models of three-dimensional objects and characters, and marks them as 1, 2, 3, ..., n in sequence;

[0009] A three-dimensional scene image information acquisition module: comprising a picture quality information acquisition unit, a rendering effect information acquisition unit and an image processing efficiency information acquisition unit, and used for selecting a first key text from the feature text data;

[0010] Data standardization processing module: used for standardizing the first key text data to obtain the second key text;

[0011] A three-dimensional image text processing module: used for importing the second key text data into the mathematical model of the picture quality coefficient, the mathematical model of the rendering effect coefficient, the mathematical model of the image processing efficiency coefficient and the mathematical model of the image processing evaluation index for analysis and processing, and obtaining any one text output value in the three-dimensional image scene determination module;

[0012] The three-dimensional image text comprehensive processing module is used to import multiple text output values ​​obtained based on the three-dimensional image text processing module into the mathematical model of the image processing comprehensive evaluation index and perform analysis and processing to obtain a comprehensive text output value;

[0013] Image processing comprehensive judgment module: used to compare the comprehensive text output value with the preset value, and input the comparison result into the interactive feedback module;

[0014] Interactive feedback module: used to output the comprehensive text output value to the user information terminal.

[0015] Preferably, the specific method for acquiring the first key text in the three-dimensional scene image information acquisition module is as follows:

[0016] It should be specifically explained in this embodiment that the first key text refers to a frame rate parameter, a QP value parameter, a grid number parameter, a texture number parameter, a horizontal pixel precision parameter, a vertical pixel precision parameter, a mean square error parameter, an average Haussdorff distance parameter, a rendering time parameter, a memory occupancy parameter, an SSIM value parameter, and a PSNR value parameter;

[0017] The frame rate parameter refers to the frame rate ;

[0018] The QP value parameter refers to the iQP value ;

[0019] The grid number parameter refers to the number of grids i ;

[0020] The texture quantity parameter refers to the texture quantity ;

[0021] The horizontal pixel accuracy parameter refers to the horizontal pixel accuracy ;

[0022] The vertical pixel accuracy parameter refers to the vertical pixel accuracy ;

[0023] The mean square error parameter refers to the mean square error ;

[0024] The average Haussdorff distance parameter refers to the average Haussdorff distance ;

[0025] The rendering time parameter refers to the rendering time ;

[0026] The memory occupancy rate parameter refers to the memory occupancy rate ;

[0027] The SSIM value parameter refers to the iSSIM value ;

[0028] The PSNR value parameter refers to the iPSNR value .

[0029] Preferably, the specific collection method of the QP value parameter is as follows:

[0030] The QP value input by the encoder during the video encoding process is the quantization parameter. The QP is a concept widely used in video encoding, which reflects the compression of spatial details. In the video encoding process, the QP value determines the balance between image quality and compression ratio.

[0031] Preferably, the specific acquisition method of the horizontal pixel accuracy parameter is as follows:

[0032] Horizontal pixel accuracy (unit: mm / pixel) = horizontal field of view width (unit: mm) / horizontal pixel number (unit: pixels).

[0033] Preferably, the specific acquisition method of the vertical pixel accuracy parameter is as follows:

[0034] Vertical pixel accuracy (unit: mm / pixel) = vertical field of view height (unit: mm) / vertical pixel number (unit: pixels).

[0035] Preferably, the specific collection method of the mean square error parameter is as follows:

[0036] The mean square error parameter is obtained by calculating the average of the sum of squares of the differences between each pixel in the image and the corresponding point in the reference image.

[0037] Preferably, the average Haussdorff distance parameter specifically refers to:

[0038] The average Haussdorff distance is an indicator to measure the fidelity of the simplified three-dimensional mesh model to the original mesh shape. It is the arithmetic average of the one-sided Haussdorff distance from the original mesh to the simplified mesh and the one-sided Haussdorff distance from the simplified mesh to the original mesh.

[0039] Preferably, the specific collection method of the SSIM value parameter is as follows:

[0040] Structural similarity = , where x and y are the two image windows to be compared, here they refer to the image windows before and after processing, respectively. and are the mean values ​​(brightness) of x and y respectively, and are the variance (contrast) of x and y respectively, is the covariance of x and y, indicating the correlation (structure) between them, and are two constants used to avoid zero denominator and ensure stability.

[0041] Preferably, the specific collection method of the PSNR value parameter is as follows:

[0042] Peak signal-to-noise ratio =10 ,in is the maximum possible pixel value of the image, Refers to the mean square error.

[0043] Preferably, the mathematical model of the picture quality coefficient is as follows:

[0044] = ,in Refers to the picture quality coefficient, Refers to the frame rate, Refers to the iQP value, refers to the number of grids, Refers to the number of textures, Refers to the horizontal pixel accuracy, Refers to the vertical pixel accuracy.

[0045] Preferably, the mathematical model of the rendering effect coefficient is as follows:

[0046] = ,in Refers to the rendering effect coefficient, Refers to the memory usage. Refers to the rendering time.

[0047] Preferably, the mathematical model of the image processing efficiency coefficient is as follows:

[0048] = ,in Refers to the image processing efficiency coefficient, refers to the mean square error, refers to the average Haussdorff distance, Refers to the iSSIM value, Refers to the iPSNR value.

[0049] Preferably, the mathematical model of the image processing comprehensive evaluation index is as follows:

[0050] = ,in Refers to the image processing evaluation index, Refers to the picture quality coefficient, Refers to the rendering effect coefficient, Refers to the image processing efficiency coefficient, , , Refers to the weight coefficient.

[0051] Preferably, the weight coefficient , , It is calculated by the entropy method, and the specific calculation steps of the entropy method are as follows:

[0052] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the original data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0053] Calculate the proportion of indicators: Calculate the proportion of the i-th sample value under the j-th indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0054] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0055] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj=1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0056] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0057] Preferably, the mathematical model of the comprehensive evaluation index of the target area hydraulic system is as follows:

[0058] = ,in Refers to the comprehensive evaluation index of image processing, Refers to the image processing evaluation index.

[0059] Preferably, the preset value is a warning value for evaluating the picture quality, rendering efficiency and processing effect of three-dimensional animation graphic image processing based on industry practical experience. When the target area image processing comprehensive evaluation index of the target area is lower than the preset value, it means that the picture quality, rendering efficiency and processing effect of the area are poor, and corresponding measures need to be taken to optimize the picture quality, rendering efficiency and processing effect of three-dimensional animation graphic image processing.

[0060] Technical effects and advantages of the present invention:

[0061] 1. The present invention realizes comprehensive monitoring of the target area through precise area division. Through the three-dimensional image scene determination module, the target area is divided into several areas, and basic information is collected in each area. The basic information includes frame rate information, QP value information, grid number information, texture number information, horizontal pixel accuracy information, vertical pixel accuracy information, mean square error information, average Haussdorff distance information, rendering time information, memory occupancy information, SSIM value information, PSNR value information, covering the three aspects of picture quality information, rendering effect information and image processing efficiency information of the three-dimensional animation graphic image processing system, thereby providing a more comprehensive and detailed monitoring means for the overall performance of the three-dimensional animation graphic image processing system;

[0062] 2. By conducting an in-depth analysis of the collected data, the present invention establishes a mathematical model that can comprehensively measure the overall performance of the 3D animation graphics and image processing system. By establishing such a comprehensive model, the present invention can better measure the overall performance of the 3D animation graphics and image processing system from different dimensions. This comprehensive evaluation method can more comprehensively understand the actual effect and performance of the 3D animation graphics and image processing system, thereby improving the overall work efficiency and quality of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0064] Figure 2 It is a schematic diagram of the structure of the three-dimensional scene image information acquisition module of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] As attached Figure 1 The three-dimensional animation graphics image processing system based on AI artificial intelligence shown in the figure includes a system operation database, a system central processing module and a user information terminal, and is characterized in that it also includes: a three-dimensional image scene determination module, a three-dimensional scene image information acquisition module, a data standardization processing module, a three-dimensional image text processing module, a three-dimensional image text comprehensive processing module, an image processing comprehensive judgment module and an interactive feedback module.

[0067] The system operation database includes all data texts of the three-dimensional animation graphic image processing system, and collects the information texts output by each module in real time. The system central processing module is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving the three-dimensional animation graphic image processing system;

[0068] The output end of the three-dimensional image scene determination module is connected to the input end of the three-dimensional scene image information acquisition module, the output end of the three-dimensional scene image information acquisition module is connected to the input end of the data standardization processing module, the output end of the data standardization processing module is connected to the input end of the three-dimensional image text processing module, the output end of the three-dimensional image text processing module is connected to the input end of the three-dimensional image text comprehensive processing module, the output end of the three-dimensional image text comprehensive processing module is connected to the input end of the image processing comprehensive judgment module, and the output end of the image processing comprehensive judgment module is connected to the input end of the interactive feedback module.

[0069] The three-dimensional image scene determination module selects feature text data based on accurate three-dimensional models of three-dimensional objects and characters, and marks them as 1, 2, 3, ..., n in sequence;

[0070] As attached Figure 2 The three-dimensional scene image information acquisition module shown includes a picture quality information acquisition unit, a rendering effect information acquisition unit and an image processing efficiency information acquisition unit, which are used to select a first key text for the feature text data;

[0071] In a preferred technical solution of the present application, the specific method for obtaining the first key text in the three-dimensional scene image information acquisition module is as follows:

[0072] It should be specifically explained in this embodiment that the first key text refers to a frame rate parameter, a QP value parameter, a grid number parameter, a texture number parameter, a horizontal pixel precision parameter, a vertical pixel precision parameter, a mean square error parameter, an average Haussdorff distance parameter, a rendering time parameter, a memory occupancy parameter, an SSIM value parameter, and a PSNR value parameter;

[0073] The frame rate parameter refers to the frame rate ;

[0074] The QP value parameter refers to the iQP value ;

[0075] The grid number parameter refers to the number of grids i ;

[0076] The texture quantity parameter refers to the texture quantity ;

[0077] The horizontal pixel accuracy parameter refers to the horizontal pixel accuracy ;

[0078] The vertical pixel accuracy parameter refers to the vertical pixel accuracy ;

[0079] The mean square error parameter refers to the mean square error ;

[0080] The average Haussdorff distance parameter refers to the average Haussdorff distance ;

[0081] The rendering time parameter refers to the rendering time ;

[0082] The memory occupancy rate parameter refers to the memory occupancy rate ;

[0083] The SSIM value parameter refers to the iSSIM value ;

[0084] The PSNR value parameter refers to the iPSNR value ;

[0085] It should be specifically noted in this embodiment that the frame rate parameter, the number of grid parameters, the number of texture parameters, the rendering time parameter, and the memory occupancy rate parameter are all obtained by conventional methods or conventional devices, such as by recording real-time data of image processing to obtain the frame rate parameter, the number of grid parameters, the rendering time parameter, and the memory occupancy rate parameter, so this embodiment does not specifically limit them;

[0086] It should be specifically explained in this embodiment that the specific collection method of the QP value parameter is as follows:

[0087] The QP value input by the encoder during the video encoding process is the quantization parameter. The QP is a concept widely used in video encoding, which reflects the compression of spatial details. In the video encoding process, the QP value determines the balance between image quality and compression ratio.

[0088] It should be specifically explained in this embodiment that the specific acquisition method of the horizontal pixel accuracy parameter is as follows:

[0089] Horizontal pixel accuracy (unit: mm / pixel) = horizontal field of view width (unit: mm) / horizontal pixel number (unit: pixels);

[0090] It should be specifically explained in this embodiment that the specific acquisition method of the vertical pixel accuracy parameter is as follows:

[0091] Vertical pixel accuracy (unit: mm / pixel) = vertical field of view height (unit: mm) / vertical pixel number (unit: pixels);

[0092] It should be specifically explained in this embodiment that the specific collection method of the mean square error parameter is as follows:

[0093] The mean square error parameter is obtained by calculating the average of the sum of squares of the differences between each pixel in the image and the corresponding point in the reference image;

[0094] It should be specifically explained in this embodiment that the average Haussdorff distance parameter specifically refers to:

[0095] The average Haussdorff distance is an indicator to measure the fidelity of the simplified three-dimensional mesh model to the original mesh shape. It is the arithmetic average of the one-sided Haussdorff distance from the original mesh to the simplified mesh and the one-sided Haussdorff distance from the simplified mesh to the original mesh.

[0096] It should be specifically explained in this embodiment that the specific collection method of the SSIM value parameter is as follows:

[0097] Structural similarity = , where x and y are the two image windows to be compared, here they refer to the image windows before and after processing, respectively. and are the mean values ​​(brightness) of x and y respectively, and are the variance (contrast) of x and y respectively, is the covariance of x and y, indicating the correlation (structure) between them, and are two constants used to avoid zero denominators and ensure stability;

[0098] It should be specifically explained in this embodiment that the specific collection method of the PSNR value parameter is as follows:

[0099] Peak signal-to-noise ratio =10 ,in is the maximum possible pixel value of the image, Refers to the mean square error;

[0100] The data standardization processing module is used to perform standardization processing on the first key text data to obtain the second key text.

[0101] The three-dimensional image text processing module is used to import the second key text data into the mathematical model of the picture quality coefficient, the mathematical model of the rendering effect coefficient, the mathematical model of the image processing efficiency coefficient and the mathematical model of the image processing evaluation index for analysis and processing, and obtain any one text output value in the three-dimensional image scene determination module;

[0102] It should be specifically explained in this embodiment that the mathematical model of the picture quality coefficient is as follows:

[0103] = ,in Refers to the picture quality coefficient, Refers to the frame rate, Refers to the iQP value, refers to the number of grids, Refers to the number of textures, Refers to the horizontal pixel accuracy, Refers to vertical pixel accuracy;

[0104] It should be specifically explained in this embodiment that the mathematical model of the rendering effect coefficient is as follows:

[0105] = ,in Refers to the rendering effect coefficient, Refers to the memory usage. Refers to the rendering time;

[0106] It should be specifically explained in this embodiment that the mathematical model of the image processing efficiency coefficient is as follows:

[0107] = ,in Refers to the image processing efficiency coefficient, refers to the mean square error, refers to the average Haussdorff distance, Refers to the iSSIM value, Refers to the iPSNR value;

[0108] It should be specifically explained in this embodiment that the mathematical model of the image processing evaluation index is as follows:

[0109] = ,in Refers to the image processing evaluation index, Refers to the picture quality coefficient, Refers to the rendering effect coefficient, Refers to the image processing efficiency coefficient, , , Refers to the weight coefficient;

[0110] It should be specifically explained in this embodiment that the weight coefficient , , It is calculated by the entropy method, and the specific calculation steps of the entropy method are as follows:

[0111] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the original data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0112] Calculate the proportion of indicators: Calculate the proportion of the i-th sample value under the j-th indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0113] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0114] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj=1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0115] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0116] The three-dimensional image text comprehensive processing module is used to import multiple text output values ​​obtained based on the three-dimensional image text processing module into the mathematical model of the image processing comprehensive evaluation index and perform analysis and processing to obtain a comprehensive text output value;

[0117] It should be specifically explained in this embodiment that the mathematical model of the target area image processing comprehensive evaluation index is as follows:

[0118] = ,in Refers to the comprehensive evaluation index of image processing, Refers to the image processing evaluation index.

[0119] The image processing comprehensive judgment module is used to compare the comprehensive text output value with the preset value and input the comparison result to the interactive feedback module;

[0120] What needs to be specifically explained in this embodiment is that the preset value is a warning value for evaluating the picture quality, rendering efficiency and processing effect of three-dimensional animation graphic image processing based on industry practical experience. When the comprehensive evaluation index of the target area image processing in the target area is lower than the preset value, it means that the picture quality, rendering efficiency and processing effect of the area are poor, and corresponding measures need to be taken to optimize the picture quality, rendering efficiency and processing effect of the three-dimensional animation graphic image processing.

[0121] The interactive feedback module is used to output the comprehensive text output value to the user information terminal;

[0122] What needs to be specifically explained in this embodiment is that when the comparison result of the interactive feedback module is lower than the preset value, the system will trigger the alarm function on the terminal, send a warning signal to the management personnel in the form of sound, vibration and pop-up window, and give relevant parameters, and use artificial intelligence to help management personnel analyze the reasons affecting the comprehensive evaluation index of image processing in the target area, and further track down specific aspects that affect the comprehensive performance, such as poor picture quality, low rendering efficiency and poor processing effect of three-dimensional animation graphic image processing.

[0123] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0124] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A 3D animation graphics and image processing system based on AI artificial intelligence, comprising a system operation database, a system central processing module and a user information terminal, characterized in that: Also includes: A three-dimensional image scene determination module, a three-dimensional scene image information acquisition module, a data standardization processing module, a three-dimensional image text processing module, a three-dimensional image text comprehensive processing module, an image processing comprehensive judgment module, and an interactive feedback module; The system operation database includes all data texts of the three-dimensional animation graphic image processing system, and collects the information texts output by each module in real time. The system central processing module is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving the three-dimensional animation graphic image processing system; The three-dimensional image scene determination module: screens feature text data based on accurate three-dimensional models of three-dimensional objects and characters, and marks them as 1, 2, 3, ..., n in sequence; The three-dimensional scene image information acquisition module includes a picture quality information acquisition unit, a rendering effect information acquisition unit and an image processing efficiency information acquisition unit, and is used to select a first key text from the feature text data; The data standardization processing module is used to perform standardization processing on the first key text data to obtain the second key text; The three-dimensional image text processing module is used to import the second key text data into the mathematical model of the picture quality coefficient, the mathematical model of the rendering effect coefficient, the mathematical model of the image processing efficiency coefficient and the mathematical model of the image processing evaluation index for analysis and processing, so as to obtain any one text output value in the three-dimensional image scene determination module; The three-dimensional image text comprehensive processing module is used to import multiple text output values ​​obtained based on the three-dimensional image text processing module into the mathematical model of the image processing comprehensive evaluation index and perform analysis and processing to obtain a comprehensive text output value; The image processing comprehensive judgment module is used to compare the comprehensive text output value with the preset value and input the comparison result to the interactive feedback module; The interactive feedback module is used to output the comprehensive text output value to the user information terminal; The mathematical model of the picture quality coefficient is as follows: = ,in Refers to the picture quality coefficient, Refers to the frame rate, Refers to the iQP value, refers to the number of grids, Refers to the number of textures, Refers to the horizontal pixel accuracy, Refers to vertical pixel accuracy; The mathematical model of the rendering effect coefficient is as follows: = ,in Refers to the rendering effect coefficient, Refers to the memory usage. Refers to the rendering time; The mathematical model of the image processing efficiency coefficient is as follows: = ,in Refers to the image processing efficiency coefficient, refers to the mean square error, refers to the average Haussdorff distance, Refers to the iSSIM value, Refers to the iPSNR value; The mathematical model of the image processing evaluation index is as follows: = ,in Refers to the image processing evaluation index, Refers to the picture quality coefficient, Refers to the rendering effect coefficient, Refers to the image processing efficiency coefficient, , , Refers to the weight coefficient.

2. The three-dimensional animation graphics and image processing system based on AI artificial intelligence according to claim 1, characterized in that: The specific method for obtaining the first key text in the three-dimensional scene image information acquisition module is as follows: The first key text refers to the frame rate parameter, QP value parameter, grid number parameter, texture number parameter, horizontal pixel accuracy parameter, vertical pixel accuracy parameter, mean square error parameter, average Haussdorff distance parameter, rendering time parameter, memory occupancy parameter, SSIM value parameter, and PSNR value parameter; The frame rate parameter refers to the frame rate ; The QP value parameter refers to the iQP value ; The grid number parameter refers to the number of grids i ; The texture quantity parameter refers to the texture quantity ; The horizontal pixel accuracy parameter refers to the horizontal pixel accuracy ; The vertical pixel accuracy parameter refers to the vertical pixel accuracy ; The mean square error parameter refers to the mean square error ; The average Haussdorff distance parameter refers to the average Haussdorff distance ; The rendering time parameter refers to the rendering time ; The memory occupancy rate parameter refers to the memory occupancy rate ; The SSIM value parameter refers to the iSSIM value ; The PSNR value parameter refers to the iPSNR value .

3. The 3D animation graphics and image processing system based on AI artificial intelligence according to claim 1, characterized in that: The mathematical model of the image processing comprehensive evaluation index is as follows: = ,in Refers to the comprehensive evaluation index of image processing, Refers to the image processing evaluation index.

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