Art painting image processing system based on image recognition

Abstract

The invention relates to the field of image processing, in particular to an art painting image processing system based on image recognition, which comprises a contour detection module, a contour comparison module, a contour restoration module, a color judgment module and a color restoration module. According to the invention, contour detection, abnormity judgment and restoration are carried out on the to-be-processed drawing image, the integrity and accuracy of contour processing are ensured, the quality of image processing is improved, through the cooperation of the color judgment module and the color restoration module, the color is further judged and restored after contour restoration is completed, and the image quality is improved. According to the method, the contour accuracy of the painting work is ensured, the color unification is also ensured, the omnibearing optimization of the painting image is realized, the image processing efficiency is obviously improved, the manual intervention is reduced, and the accuracy of the painting image and the painting quality are improved.

Description

Technical Field

[0001] The present invention relates to the field of image processing, and in particular to an art painting image processing system based on image recognition. Background Art

[0002] In the process of painting teaching and creation, learners often need to imitate or copy standard works. In this process, learners may deviate in the accuracy of contours, the continuity of lines, and the use of colors. The standard works used by learners to imitate are mostly produced on an assembly line basis. There is a lack of quality inspection and restoration methods for painting images, resulting in uneven standards and difficulty in meeting the special requirements of teaching consistency.

[0003] In the field of art creation and restoration, professionals often need to conduct detailed analysis and restoration of paintings. These tasks usually require a lot of time and expertise, and are easily affected by personal subjective judgment. When the quality of the reference standards varies, the analysis of paintings becomes even more difficult.

[0004] This shows the following problem: In the prior art, it is impossible to accurately detect and repair the quality of fine art paintings, resulting in low quality and poor accuracy of painting production. Summary of the invention

[0005] To this end, the present invention provides an art painting image processing system based on image recognition, which is used to overcome the problem of low quality and poor accuracy of painting production caused by the inability to accurately detect and repair the painting quality of art paintings in the prior art by judging and correcting the painting contour and color.

[0006] To achieve the above object, the present invention provides an art painting image processing system based on image recognition, comprising:

[0007] A contour detection module is used to detect the contours of the color-filled areas of the to-be-processed painting image and the standard painting image, and obtain the to-be-processed contour line and the standard contour line;

[0008] A contour repair module, which is connected to the contour comparison module, and is used to detect whether the contour line to be processed has a break when there is no abnormal area. If there is a break, the break is repaired according to the standard contour line to obtain an image to be verified;

[0009] A color determination module, connected to the contour restoration module, for performing color determination on the color block of the image to be verified;

[0010] The color restoration module is connected to the color determination module and is used to restore the color of the color block to be processed according to the color of the standard color block in the standard painting image when the color of the color block to be processed is different from the color of the standard painting block corresponding to the standard painting image.

[0011] Furthermore, the contour detection module comprises:

[0012] A contour optimization unit, used for denoising the painting image to be processed to remove noise, and performing edge sharpening to improve the image edge clarity, so as to obtain an optimized standard painting image;

[0013] The contour extraction unit is connected to the contour optimization unit and is used to process the to-be-inspected painting image and the optimized standard painting image respectively to obtain corresponding to-be-processed contour lines and standard contour lines.

[0014] Furthermore, the contour comparison module includes:

[0015] A contour registration unit, used for spatially registering the contour line to be processed with the standard contour line so that the two correspond to each other in the same coordinate system;

[0016] A grid division unit connected to the contour registration unit, for performing the same grid division on the contour line to be processed and the standard contour line to obtain a plurality of grids to be inspected and a plurality of standard grids;

[0017] a difference comparison unit connected to the grid division unit, for comparing the area to be verified in the grid to be verified with the standard area in the corresponding standard grid to determine whether the grid to be verified is abnormal;

[0018] An abnormality determination unit is connected to the difference comparison unit and is used to determine whether the contour is abnormal based on the number of abnormalities of the grid to be verified.

[0019] Furthermore, the grid division unit includes:

[0020] Line setting subunit, used to set the same number of horizontal and vertical axis lines in the coordinate system:

[0021] The grid setting subunit is connected to the line setting subunit and is used to divide the contour line to be processed and the standard contour line into corresponding grids to be checked and standard grids according to the horizontal axes and the vertical axes to obtain grid segments to be verified and standard grid segments.

[0022] Furthermore, the difference comparison unit includes:

[0023] An area calculation subunit, used for calculating the area to be verified of the contour segment to be verified in any of the grids to be verified and the standard area of ​​the standard contour segment in any of the standard grids in the standard grid;

[0024] an area comparison subunit, which is connected to the area calculation subunit and is used to compare the area to be verified with the standard area to obtain a comparison result;

[0025] The abnormality determination subunit is connected to the area comparison subunit and is used to determine whether the grid to be verified is abnormal according to the comparison result.

[0026] Furthermore, the abnormality determination unit includes:

[0027] An abnormality number calculation subunit, used to calculate the abnormality number of the to-be-verified grids that are determined to be abnormal;

[0028] The abnormality determination subunit is connected to the abnormality number calculation subunit, and is used to compare the abnormality number with a preset standard abnormality number, and determine that the contour is abnormal when the abnormality number is greater than the standard abnormality number.

[0029] Furthermore, the contour repair module includes:

[0030] A fracture detection unit, used to detect whether the contour line to be processed has fractures, and if so, determine it as an image to be repaired;

[0031] A fracture positioning unit, connected to the fracture detection unit, for locating a fracture to-be-verified grid corresponding to a fracture contour line;

[0032] A contour repairing unit is connected to the fracture locating unit and is used to repair the fracture contour line according to a standard contour line in a corresponding standard grid in the standard grid corresponding to the fractured grid to be verified.

[0033] Furthermore, the color determination module includes:

[0034] A picture block segmentation unit, used for segmenting the to-be-processed painting image and the standard painting image into a corresponding number of to-be-processed color blocks and a number of standard color blocks;

[0035] A difference determination unit is connected to the picture block segmentation unit and is used to determine whether there is a color difference between the to-be-processed color block and the corresponding standard color block.

[0036] Furthermore, the difference determination unit includes:

[0037] A color extraction subunit, used to extract the color to be verified of the color block to be processed and the standard color of the corresponding standard color block;

[0038] The difference determination subunit is connected to the color extraction subunit and is used to determine whether there is a color difference based on the color to be verified and the standard color.

[0039] Furthermore, the color restoration module includes:

[0040] A repair area determination unit, used to determine a color block to be repaired according to a determination result of the difference determination unit;

[0041] A color restoration unit is connected to the restoration area determination unit and is used to perform color restoration on the color block to be restored according to the standard color.

[0042] Compared with the prior art, the beneficial effect of the present invention lies in that, by performing contour detection, abnormality judgment and repair on the painting image to be processed, the integrity and accuracy of contour processing are ensured, and the quality of image processing is improved. Through the cooperation of the color judgment module and the color repair module, the color is further judged and repaired after the contour repair is completed, which not only ensures the accuracy of the contour of the painting work, but also ensures the uniformity of color, realizes all-round optimization of the painting image, significantly improves the efficiency of image processing, reduces manual intervention, and improves the accuracy of the painting image and the painting quality.

[0043] Furthermore, the interference information in the image is effectively removed through denoising, and the edge sharpening operation improves the clarity of the image edges. These two pre-processing steps significantly improve the overall quality of the image and lay a solid foundation for subsequent contour extraction. Since the optimized image has clearer edges and less noise, the contour extraction unit can more accurately identify and extract the contour lines in the image, which not only improves the accuracy of contour extraction, but also reduces the possibility of misjudgment and missed judgment, thereby improving the processing efficiency of the entire system.

[0044] Furthermore, by making the contour line to be processed correspond to the standard contour line in the same coordinate system, the accuracy of subsequent comparison is ensured, laying the foundation for accurate contour comparison. The grid division unit divides the contour line into several grids, realizing localized analysis of the contour, and can accurately locate the specific position of the contour difference, rather than just making an overall comparison, which greatly improves the accuracy and detail of the comparison, and improves the accuracy and efficiency of the judgment.

[0045] Furthermore, by setting the same number of horizontal and vertical axes in the coordinate system, the contour lines to be processed and the standard contour lines are divided into corresponding grids, thereby achieving a refined comparison of the contour lines. By adjusting the number of horizontal and vertical axes, the size of the grid can be flexibly controlled, so that the system can dynamically adjust the analysis accuracy according to different image complexities and accuracy requirements, thereby adapting to various types of painting images, greatly improving the processing speed as well as the precision and accuracy of contour comparison.

[0046] Furthermore, by dividing the contour line into grids and calculating the area within each grid, a refined comparison of the contours is achieved, which can better capture subtle differences and judge the degree of abnormality of the contour more objectively and accurately, greatly improving the accuracy of anomaly detection. Grid processing allows the system to calculate the area of ​​each grid in parallel and make comparisons, improving processing efficiency.

[0047] Furthermore, by adjusting the preset number of standard anomalies, the system can flexibly adapt to paintings of different types or with different requirements. This adjustable judgment standard enables the system to cope with various complex practical application scenarios, enhancing the adaptability and versatility of the system. By introducing the calculation of the number of anomalies and the comparison of the standard number of anomalies, the judgment result can be quickly obtained, which helps to improve the system's processing capabilities for various input images.

[0048] Furthermore, by mapping the broken contour line to the corresponding grid to be verified, the broken part in the contour line to be processed can be accurately identified, unnecessary processing of the complete contour can be avoided, the accuracy of positioning can be improved, a clear reference can be provided for the subsequent repair process, highly precise contour repair can be achieved, and the working efficiency and accuracy of the system can be improved.

[0049] Furthermore, by dividing the painting image to be processed and the standard painting image into corresponding color blocks, the color differences can be accurately located, parallel computing is realized, and the processing efficiency is significantly improved. By individually judging each color block, the restoration process can specifically process each color block with differences, greatly improving the accuracy and detail of color judgment.

[0050] Furthermore, by respectively extracting the color information of the color block to be processed and the standard color block, the color features can be accurately acquired, making the color comparison process more standardized and efficient, quickly and accurately identifying the color block that needs to be repaired, and improving the accuracy of color difference judgment and processing efficiency.

[0051] Furthermore, by accurately locating the color block that needs to be repaired according to the result of the difference determination unit, it is ensured that the repair process is only targeted at the area where color anomalies actually exist, avoiding unnecessary intervention in normal areas, and improving the pertinence and efficiency of the repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a system framework diagram of an art painting image processing system based on image recognition according to an embodiment of the present invention;

[0053] Figure 2 It is a structural schematic diagram of a contour detection module according to an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the structure of a profile comparison module according to an embodiment of the present invention;

[0055] Figure 4 It is a schematic diagram of the structure of the contour repair module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; 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.

[0057] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0058] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0059] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0060] See also Figure 1 ,like Figure 1 As shown, it is a system framework diagram of an art painting image processing system based on image recognition according to an embodiment of the present invention;

[0061] Specifically, the art painting image processing system based on image recognition provided by the embodiment of the present invention includes:

[0062] A contour detection module is used to detect the contours of the color-filled areas of the to-be-processed painting image and the standard painting image, and obtain the to-be-processed contour line and the standard contour line;

[0063] A contour repair module, which is connected to the contour comparison module, and is used to detect whether the contour line to be processed has a break when there is no abnormal area. If there is a break, the break is repaired according to the standard contour line to obtain an image to be verified;

[0064] A color determination module, connected to the contour restoration module, for performing color determination on the color block of the image to be verified;

[0065] The color restoration module is connected to the color determination module and is used to restore the color of the color block to be processed according to the color of the standard color block in the standard painting image when the color of the color block to be processed is different from the color of the standard painting block corresponding to the standard painting image.

[0066] Specifically, the contour lines of the produced colored painting images in the colored area are detected to obtain their contour lines, and the contour lines of the produced painting images are verified according to the standard contour lines. If there are any abnormalities, it means that the product is unqualified and needs to be screened out. If there are no abnormalities, it is necessary to detect whether the contour is complete and whether there are any missing parts. If there are any missing parts, they can be supplemented according to the standard. When there is no problem with the contour, the color is further determined to determine whether there are any color printing errors. If so, reprint and repair them.

[0067] Specifically, by performing contour detection, anomaly judgment and repair on the painting image to be processed, the integrity and accuracy of contour processing are ensured and the quality of image processing is improved. Through the cooperation of the color judgment module and the color repair module, the color is further judged and repaired after the contour repair is completed, which not only ensures the accuracy of the contour of the painting, but also ensures the uniformity of color, realizes the all-round optimization of the painting image, significantly improves the efficiency of image processing, reduces manual intervention, and improves the accuracy and quality of the painting image.

[0068] Please continue reading Figure 2 ,like Figure 2 As shown, it is a schematic diagram of the structure of the contour detection module according to an embodiment of the present invention;

[0069] Specifically, the contour detection module includes:

[0070] A contour optimization unit, used for denoising the painting image to be processed to remove noise, and performing edge sharpening to improve the image edge clarity, so as to obtain an optimized standard painting image;

[0071] The contour extraction unit is connected to the contour optimization unit and is used to process the to-be-inspected painting image and the optimized standard painting image respectively to obtain corresponding to-be-processed contour lines and standard contour lines.

[0072] Specifically, the noise of the painting image to be processed is removed to optimize the image. This is a prior art and will not be described in detail here. The edges are sharpened to make the image contour more obvious. The contour lines to be detected of the painting image to be processed are extracted through image processing, and the standard contour lines of the standard image are also extracted.

[0073] Specifically, the denoising process effectively removes interference information from the image, while the edge sharpening operation improves the clarity of the image edges. These two preprocessing steps significantly improve the overall quality of the image and lay a solid foundation for subsequent contour extraction. Since the optimized image has clearer edges and less noise, the contour extraction unit can more accurately identify and extract contour lines in the image, which not only improves the accuracy of contour extraction, but also reduces the possibility of misjudgment and missed judgment, thereby improving the processing efficiency of the entire system.

[0074] Please continue reading Figure 3 ,like Figure 3 As shown, it is a schematic diagram of the structure of the profile comparison module according to an embodiment of the present invention;

[0075] Specifically, the contour comparison module includes:

[0076] A contour registration unit, used for spatially registering the contour line to be processed with the standard contour line so that the two correspond to each other in the same coordinate system;

[0077] A grid division unit connected to the contour registration unit, for performing the same grid division on the contour line to be processed and the standard contour line to obtain a plurality of grids to be inspected and a plurality of standard grids;

[0078] a difference comparison unit connected to the grid division unit, for comparing the area to be verified in the grid to be verified with the standard area in the corresponding standard grid to determine whether the grid to be verified is abnormal;

[0079] An abnormality determination unit is connected to the difference comparison unit and is used to determine whether the contour is abnormal based on the number of abnormalities of the grid to be verified.

[0080] Specifically, the contour line to be processed and the standard contour line are set at the same coordinate, and the two correspond to each other. The contour line to be processed and the standard contour line are divided into a corresponding number of grids to be inspected and a number of standard grids by setting a number of horizontal axes and a number of vertical axes. The image areas formed by the contour line to be verified and the standard contour line and the grid lines are calculated to determine whether the contour is abnormal.

[0081] Specifically, by making the contour line to be processed correspond to the standard contour line in the same coordinate system, the accuracy of subsequent comparison is ensured, laying the foundation for accurate contour comparison. The grid division unit divides the contour line into several grids, realizing localized analysis of the contour, and can accurately locate the specific position of the contour difference, rather than just making an overall comparison, which greatly improves the accuracy and detail of the comparison, and improves the accuracy and efficiency of the judgment.

[0082] Specifically, the grid division unit includes:

[0083] Line setting subunit, used to set the same number of horizontal and vertical axis lines in the coordinate system:

[0084] The grid setting subunit is connected to the line setting subunit and is used to divide the contour line to be processed and the standard contour line into corresponding grids to be checked and standard grids according to the horizontal axes and the vertical axes to obtain grid segments to be verified and standard grid segments.

[0085] In the specific implementation process, a number of horizontal axes and a number of vertical axes with a mutual interval of 1 mm are set for the contour line to be processed and the standard contour line, and the inspection contour line and the standard contour line are divided into a number of grid segments to be verified and a number of standard grid segments.

[0086] Specifically, by setting the same number of horizontal and vertical axes in the coordinate system, the contour lines to be processed and the standard contour lines are divided into corresponding grids, thereby achieving a refined comparison of the contour lines. By adjusting the number of horizontal and vertical axes, the size of the grid can be flexibly controlled, so that the system can dynamically adjust the analysis accuracy according to different image complexities and accuracy requirements, thereby adapting to various types of painting images, greatly improving the processing speed as well as the precision and accuracy of contour comparison.

[0087] Specifically, the difference comparison unit includes:

[0088] An area calculation subunit, used for calculating the area to be verified of the contour segment to be verified in any of the grids to be verified and the standard area of ​​the standard contour segment in any of the standard grids in the standard grid;

[0089] an area comparison subunit, which is connected to the area calculation subunit and is used to compare the area to be verified with the standard area to obtain a comparison result;

[0090] The abnormality determination subunit is connected to the area comparison subunit and is used to determine whether the grid to be verified is abnormal according to the comparison result.

[0091] Specifically, the area to be verified composed of each contour segment to be verified and the grid lines is calculated and compared with the standard area composed of the corresponding standard contour segment and grid lines. If the area to be verified is different from the standard area, the grid to be verified is determined to be abnormal. In the specific implementation, the area to be verified composed of a contour segment to be verified and the grid lines is calculated to be 0.5mm, and the standard area composed of the standard contour segment and the grid lines corresponding to the contour segment to be verified is 0.6mm, then the grid to be verified is determined to be abnormal.

[0092] Specifically, by dividing the contour line into grids and calculating the area within each grid, a refined comparison of the contour is achieved, which can capture subtle differences and judge the degree of abnormality of the contour more objectively and accurately, greatly improving the accuracy of anomaly detection. Grid processing allows the system to calculate the area of ​​each grid and make comparisons in parallel, improving processing efficiency.

[0093] Specifically, the abnormality determination unit includes:

[0094] An abnormality number calculation subunit, used to calculate the abnormality number of the to-be-verified grids that are determined to be abnormal;

[0095] The abnormality determination subunit is connected to the abnormality number calculation subunit, and is used to compare the abnormality number with a preset standard abnormality number, and determine that the contour is abnormal when the abnormality number is greater than the standard abnormality number.

[0096] In the specific implementation process, the preset standard anomaly number is 20, the anomaly number of a contour line to be verified is 30, and the anomaly number is greater than the standard anomaly number, and the contour is determined to be abnormal.

[0097] Specifically, by adjusting the preset number of standard anomalies, the system can flexibly adapt to paintings of different types or with different requirements. This adjustable judgment standard enables the system to cope with various complex practical application scenarios, enhancing the adaptability and versatility of the system. By introducing the calculation of the number of anomalies and the comparison of the standard number of anomalies, the judgment results can be quickly obtained, which helps to improve the system's processing capabilities for various input images.

[0098] Please continue reading Figure 4 ,like Figure 4 As shown, it is a schematic diagram of the structure of the contour repair module according to an embodiment of the present invention;

[0099] Specifically, the contour repair module includes:

[0100] A fracture detection unit, used to detect whether the contour line to be processed has fractures, and if so, determine it as an image to be repaired;

[0101] A fracture positioning unit, connected to the fracture detection unit, for locating a fracture to-be-verified grid corresponding to a fracture contour line;

[0102] A contour repairing unit is connected to the fracture locating unit and is used to repair the fracture contour line according to a standard contour line in a corresponding standard grid in the standard grid corresponding to the fractured grid to be verified.

[0103] In the specific implementation process, when the contour is not abnormal, the contour line to be processed is processed and the pixel continuity is checked to determine whether there is a break in the contour line. It can be understood that the continuity of the contour line can also be other methods such as algorithm tracking, which is not limited here. When it is determined that there is a break, the break is fitted and repaired according to the standard contour line in the standard grid corresponding to the grid to be verified where the break is located.

[0104] Specifically, by mapping the broken contour line to the corresponding grid to be verified, the broken part in the contour line to be processed can be accurately identified, unnecessary processing of the complete contour can be avoided, the accuracy of positioning can be improved, a clear reference can be provided for the subsequent repair process, highly precise contour repair can be achieved, and the work efficiency and accuracy of the system can be improved.

[0105] Specifically, the color determination module includes:

[0106] A picture block segmentation unit, used for segmenting the to-be-processed painting image and the standard painting image into a corresponding number of to-be-processed color blocks and a number of standard color blocks;

[0107] A difference determination unit is connected to the picture block segmentation unit and is used to determine whether there is a color difference between the to-be-processed color block and the corresponding standard color block.

[0108] Specifically, after the outline of the painting image to be verified is correct, its specific color distribution is checked, and the color of the color block to be processed in the painting image to be processed is compared with the color of the standard color block in the corresponding standard painting image to determine whether there is a difference in the color of the color block.

[0109] Specifically, by dividing the painting image to be processed and the standard painting image into corresponding color blocks, the color differences can be accurately located, parallel computing is realized, and the processing efficiency is significantly improved. By individually judging each color block, the restoration process can specifically process each color block with differences, greatly improving the accuracy and detail of color judgment.

[0110] This is especially important to ensure the accuracy and authenticity of the artwork.

[0111] Specifically, the difference determination unit includes:

[0112] A color extraction subunit, used to extract the to-be-verified color of the to-be-processed color block and the standard color of the corresponding standard color block;

[0113] The difference determination subunit is connected to the color extraction subunit and is used to determine whether there is a color difference based on the color to be verified and the standard color.

[0114] In a specific implementation process, if the color to be verified and the standard color of a certain color block are both red, it is determined that there is no abnormality.

[0115] Specifically, by extracting the color information of the color block to be processed and the standard color block respectively, the color features can be accurately acquired, making the color comparison process more standardized and efficient, quickly and accurately identifying the color blocks that need to be repaired, and improving the accuracy of color difference judgment and processing efficiency.

[0116] Specifically, the color restoration module includes:

[0117] A repair area determination unit, used to determine a color block to be repaired according to a determination result of the difference determination unit;

[0118] A color restoration unit is connected to the restoration area determination unit and is used to perform color restoration on the color block to be restored according to the standard color.

[0119] In a specific implementation process, the to-be-processed color of a color block to be processed is extracted to be red, and the standard color is blue. If the color is determined to be abnormal, the color block to be processed is repaired to blue.

[0120] Specifically, by accurately locating the color block that needs to be repaired based on the results of the difference determination unit, it is ensured that the repair process only targets the area where color anomalies actually exist, avoiding unnecessary intervention in normal areas, and improving the pertinence and efficiency of the repair.

[0121] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0122] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An art painting image processing system based on image recognition, characterized in that: include: A contour detection module is used to detect the contours of the color-filled areas of the to-be-processed painting image and the standard painting image, and obtain the to-be-processed contour line and the standard contour line; A contour comparison module, connected to the contour detection module, for comparing the contour line to be processed with the standard contour line to determine whether the contour of the color-filled area is abnormal; A contour repair module, which is connected to the contour comparison module, and is used to detect whether the contour line to be processed has a break when there is no abnormal area. If there is a break, the break is repaired according to the standard contour line to obtain an image to be verified; A color determination module, connected to the contour restoration module, for performing color determination on the color block of the image to be verified; The color restoration module is connected to the color determination module and is used to restore the color of the color block to be processed according to the color of the standard color block in the standard painting image when the color of the color block to be processed is different from the color of the standard painting block corresponding to the standard painting image.

2. The art painting image processing system based on image recognition according to claim 1 is characterized in that: The contour detection module comprises: A contour optimization unit, used for denoising the painting image to be processed to remove noise, and performing edge sharpening to improve the image edge clarity, so as to obtain an optimized standard painting image; The contour extraction unit is connected to the contour optimization unit and is used to process the to-be-inspected painting image and the optimized standard painting image respectively to obtain corresponding to-be-processed contour lines and standard contour lines.

3. The art painting image processing system based on image recognition according to claim 1, characterized in that: The contour comparison module comprises: A contour registration unit, used for spatially registering the contour line to be processed with the standard contour line so that the two correspond to each other in the same coordinate system; A grid division unit connected to the contour registration unit, for performing the same grid division on the contour line to be processed and the standard contour line to obtain a plurality of grids to be inspected and a plurality of standard grids; a difference comparison unit connected to the grid division unit, for comparing the area to be verified in the grid to be verified with the standard area in the corresponding standard grid to determine whether the grid to be verified is abnormal; An abnormality determination unit is connected to the difference comparison unit and is used to determine whether the contour is abnormal based on the number of abnormalities of the grid to be verified.

4. The art painting image processing system based on image recognition according to claim 3 is characterized in that: The grid division unit comprises: Line setting subunit, used to set the same number of horizontal and vertical axis lines in the coordinate system: The grid setting subunit is connected to the line setting subunit and is used to divide the contour line to be processed and the standard contour line into corresponding grids to be checked and standard grids according to the horizontal axes and the vertical axes to obtain grid segments to be verified and standard grid segments.

5. The art painting image processing system based on image recognition according to claim 3 is characterized in that: The difference comparison unit comprises: An area calculation subunit, used for calculating the area to be verified of the contour segment to be verified in any of the grids to be verified and the standard area of ​​the standard contour segment in any of the standard grids in the standard grid; an area comparison subunit, which is connected to the area calculation subunit and is used to compare the area to be verified with the standard area to obtain a comparison result; The abnormality determination subunit is connected to the area comparison subunit and is used to determine whether the grid to be verified is abnormal according to the comparison result.

6. The art painting image processing system based on image recognition according to claim 3 is characterized in that: The abnormality determination unit comprises: An abnormality number calculation subunit, used to calculate the abnormality number of the to-be-verified grids that are determined to be abnormal; The abnormality determination subunit is connected to the abnormality number calculation subunit and is used to compare the abnormality number with a preset standard abnormality number, and determine that the contour is abnormal when the abnormality number is greater than the standard abnormality number.

7. The art painting image processing system based on image recognition according to claim 1, characterized in that: The contour repair module comprises: A fracture detection unit, used to detect whether the contour line to be processed has fractures, and if so, determine it as an image to be repaired; A fracture positioning unit, connected to the fracture detection unit, for locating a fracture to-be-verified grid corresponding to a fracture contour line; A contour repairing unit is connected to the fracture locating unit and is used to repair the fracture contour line according to a standard contour line in a corresponding standard grid in the standard grid corresponding to the fractured grid to be verified.

8. The art painting image processing system based on image recognition according to claim 1, characterized in that: The color determination module comprises: A picture block segmentation unit, used for segmenting the to-be-processed painting image and the standard painting image into a corresponding number of to-be-processed color blocks and a number of standard color blocks; A difference determination unit is connected to the picture block segmentation unit and is used to determine whether there is a color difference between the to-be-processed color block and the corresponding standard color block.

9. The art painting image processing system based on image recognition according to claim 8, characterized in that: The difference determination unit comprises: A color extraction subunit, used to extract the to-be-verified color of the to-be-processed color block and the standard color of the corresponding standard color block; The difference determination subunit is connected to the color extraction subunit and is used to determine whether there is a color difference based on the color to be verified and the standard color.

10. The art painting image processing system based on image recognition according to claim 9, characterized in that: The color restoration module comprises: A repair area determination unit, used to determine a color block to be repaired according to a determination result of the difference determination unit; A color restoration unit is connected to the restoration area determination unit and is used to perform color restoration on the color block to be restored according to the standard color.

Images