Garment quality judgment method and system based on visual data analysis

Abstract

The invention discloses a garment quality judgment method and system based on visual data analysis, relates to the technical field of garment production line monitoring, and particularly discloses a method for performing contour edge identification and part marking, screening out a garment contour and an internal detail edge by using gray features, and marking each part; then carrying out preliminary quality evaluation, and carrying out preliminary judgment on the clothes quality by analyzing edge shapes, gray features and the like; if the evaluation result does not meet the standard, triggering quality alarm, and accurately shooting the alarm garment to obtain a comparison image; and finally, performing flaw comparison and confirmation, comparing a comparison image with a preset gray scale reference image, and determining gray scale difference characteristics, thereby accurately judging the type and severity of the flaw. According to the scheme, automation, high efficiency and precision of garment quality detection are realized, the problems of low efficiency, large subjective judgment influence and the like of a traditional manual quality detection mode are effectively solved, and the accuracy and consistency of garment quality detection are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of clothing production line monitoring, and in particular to a clothing quality judgment method and system based on visual data analysis. Background Art

[0002] In the field of clothing manufacturing, quality control is the core link to ensure the final quality of products, improve consumer satisfaction and maintain brand reputation. However, current clothing quality inspection faces multiple challenges: traditional manual quality inspection methods are inefficient and difficult to meet the needs of modern fast-paced and high-volume production, and are easily affected by the subjective judgment of inspectors, resulting in inconsistent test results and high misjudgment rates; clothing defects are of various types and shapes, and traditional inspection methods are difficult to accurately identify and classify various defects; at the same time, clothing quality inspection standards are diverse and not unified, making it difficult to compare and evaluate test results horizontally; in addition, as consumers' requirements for clothing quality are increasing, quality inspection needs to be more refined and real-time, and traditional methods often cannot meet this demand. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for judging the quality of clothing that can cope with the rapid production of clothing production lines.

[0004] The present invention discloses a method for judging clothing quality based on visual data analysis, comprising: The clothing is laid flat on a shooting background board, and the clothing on the shooting background board is photographed by a shooting module to obtain a clothing surface image, the clothing surface image is preprocessed, and a plurality of edges on the clothing in the clothing surface image are determined by edge detection technology; Analyze the grayscale features beside each edge, use the grayscale features and the grayscale features of the shooting background plate as the screening conditions, screen out the clothing outline edge, determine the part to which the clothing outline edge belongs based on the length and shape of the clothing outline edge and the relationship between adjacent clothing outline edges, and mark the part to which it belongs, analyze the distance features between other edges and the clothing outline edge, determine the part to which other edges belong, record them as the inner edge of the clothing, and mark the part to which they belong; Analyze the shape features of the garment contour edge and the inner edge of the garment to obtain a first analysis result, and analyze the grayscale features of the garment contour edge and the inner edge of the garment to obtain a second analysis result, and determine a first quality assessment of the garment based on the first analysis result and the second analysis result; If the first quality evaluation result is less than or equal to the preset value, a quality alarm is issued for the corresponding clothing, the clothing with the quality alarm is accurately laid out at the designated position of the shooting background plate, and the direction of the clothing is accurately adjusted, and the clothing on the background plate is photographed again by using the shooting module to obtain a clothing comparison image, and the clothing comparison image is grayed to obtain a clothing gray comparison map; The clothing grayscale comparison image is compared with the preset clothing grayscale reference image to determine the grayscale difference characteristics between the two, and based on the performance of the grayscale difference characteristics, the defects on the clothing are determined.

[0005] In some embodiments disclosed in the present invention, a method for determining a plurality of edges on a garment in a garment surface image using edge detection technology includes: Preprocess the clothing surface image, including removing noise and enhancing contrast, and use edge detection algorithm to calculate the gradient of each pixel, and determine the edge position point according to the size and direction of the gradient; Connect several edge positions whose adjacent distances are less than or equal to a preset value to obtain a linear edge.

[0006] In some embodiments disclosed in the present invention, based on the length and shape of the edge of the garment outline and the relationship between adjacent garment outline edges, the method for determining the part to which the edge of the garment outline belongs includes: A reference garment outline diagram is set for the garments that need to be judged for quality. The reference garment outline diagram includes a plurality of reference contour edges, and a reference edge length is set for each reference contour edge. Based on the length difference between the contour edge length of each garment contour edge and the reference edge length, all garment contour edges are mapped to corresponding positions on the garment contour map, and if there are several garment contour edges whose contour edge lengths all satisfy the mapping condition for the same reference contour edge, the operation of mapping all garment contour edges to the garment contour map is performed several times to form several contour mapping maps; Based on the inter-image similarity parameter between the contour mapping image and the reference clothing contour image, the most similar contour mapping image is selected, and based on the mapping relationship between the most similar contour mapping image and the clothing contour image, the location of each clothing contour edge on the most similar contour mapping image is determined.

[0007] In some embodiments disclosed in the present invention, a method for determining an inter-image similarity parameter between a contour map and a reference garment contour map includes: Comparing the length difference between each garment outline edge and the reference outline edge, and determining the first shape similarity parameter of the garment outline edge and the reference outline edge based on the length difference; Analyze the shape matching parameters of the clothing contour edge and the reference contour edge, and based on the shape matching parameters, correct the first shape similarity parameter to obtain the second shape similarity parameter, and combine the second shape similarity parameters of other clothing contour edges beside the clothing contour edge to correct the second shape similarity parameter to obtain the third shape similarity parameter; Calculate the sum of the third similarity parameters of all clothing contour edges and identify it as the inter-image similarity parameter; Among them, the expression for calculating similar parameters between graphs is: ; Among them, the expression for calculating the third shape parameter of the clothing contour edge is: ; The expression for calculating the second shape parameter is: ; in, is the shape parameter between the figures, is the third shape parameter corresponding to the edge of the i-th clothing contour, is the number of garment outline edges, is the second similarity parameter of the previous clothing contour edge of the i-th clothing contour edge, is the second similarity parameter of the next clothing contour edge after the i-th clothing contour edge, is the influence adjustment coefficient of the second shape parameter, is the second shape parameter affecting the adjustment constant, To preset the minimum second shape parameter, is the preset standard length difference, is the absolute value of the length difference between the edge of the garment contour and the edge of the reference contour, is the shape matching parameter between the edge of the garment contour and the edge of the reference contour, is the adjustment coefficient of shape matching parameter influence, Adjustment constant for shape fit parameter effects.

[0008] In some embodiments disclosed in the present application, the method for determining the shape matching parameter of the edge of the garment contour and the edge of the reference contour includes: Two parallel contour lines are set for the reference contour edge, and the two sides of the reference contour edge are set, and the block between the parallel contour lines is identified as the reference contour edge block; The edge length of the garment contour edge falling into the reference contour edge block is identified as the shape matching parameter.

[0009] In some embodiments disclosed in the present invention, the method of analyzing the shape characteristics of the edge of the garment outline and the inner edge of the garment to obtain the first analysis result includes: Comparing the garment outline edge and the garment inner edge with respective preset standards, determining the garment outline edge or the garment inner edge that does not match the standard, and marking it as a defective edge; The method of analyzing the grayscale features of the edge of the clothing outline and the side of the inner edge of the clothing to obtain the second analysis result includes: A preset standard clothing grayscale image is set for clothing, and based on the clothing outline edge and the clothing inner edge, a standard part grayscale block for comparison on the standard clothing grayscale image is determined; The grayscale extraction of the edge of the clothing contour and the side of the inner edge of the clothing is performed to obtain the grayscale block of the comparison part, and the grayscale block of the comparison part is compared with the grayscale block of the standard part. If the difference characteristics between the two meet the preset standards, the clothing part corresponding to the grayscale block is identified as the defective clothing part.

[0010] In some embodiments disclosed in the present invention, a first quality assessment of the garment is determined based on the first analysis result and the second analysis result: Based on the first analysis result and the second analysis result, defective edges and defective blocks on the clothing are determined, and based on the number of defective edges and defective blocks, a first quality assessment of the clothing is determined.

[0011] In some embodiments disclosed in the present invention, the method of comparing a clothing grayscale comparison image with a preset clothing grayscale reference image includes: A probe point mapping array is set for the clothing grayscale comparison image and the clothing grayscale reference image, respectively. The probe point mapping array includes a plurality of grayscale probe points. The grayscale values ​​corresponding to the same grayscale probe point on the clothing grayscale comparison image and the clothing grayscale reference image are extracted, respectively, and recorded as the first grayscale value and the second grayscale value, and the combination of the first grayscale value and the second grayscale value is recorded as a comparison grayscale value group. Each comparison grayscale value group corresponds to a grayscale probe point. If the grayscale value difference in the comparison grayscale value group corresponding to each grayscale probe point is greater than or equal to a preset value, the comparison grayscale value group is identified as an abnormal comparison grayscale value group, and the grayscale probe point is marked as an abnormal grayscale probe point. A plurality of scanning blocks are randomly projected on the probe point mapping array. If the number of abnormal grayscale probe points in the same scanning block is greater than or equal to a preset value, the scanning block is marked as a defective scanning block. The defect scanning block is mapped onto the grayscale comparison image of the clothing to show the defects on the clothing.

[0012] In some embodiments disclosed in the present invention, there is also disclosed a clothing quality judgment system based on visual data analysis, comprising: The first module is used to lay the clothing on the shooting background board, and use the shooting module to shoot the clothing on the shooting background board to obtain the clothing surface image, pre-process the clothing surface image, and use the edge detection technology to determine a number of edges on the clothing in the clothing surface image; The second module is used to analyze the grayscale features beside each edge, and use the grayscale features and the grayscale features of the shooting background plate as the screening conditions to screen out the clothing outline edges, determine the parts to which the clothing outline edges belong based on the length and shape of the clothing outline edges and the relationship between the adjacent clothing outline edges, and mark the parts to which they belong, analyze the distance features between other edges and the clothing outline edges, determine the parts to which other edges belong, record them as the inner edges of the clothing, and mark the parts to which they belong; The third module is used to analyze the shape characteristics of the clothing contour edge and the inner edge of the clothing to obtain a first analysis result, and to analyze the grayscale characteristics of the clothing contour edge and the side of the inner edge of the clothing to obtain a second analysis result, and to determine a first quality evaluation of the clothing based on the first analysis result and the second analysis result; The fourth module is used for, if the first quality evaluation result is less than or equal to the preset value, issuing a quality alarm for the corresponding clothing, precisely laying the clothing with the quality alarm on a designated position of the shooting background plate, and precisely adjusting the direction of the clothing, using the shooting module to shoot the clothing on the background plate again to obtain a clothing comparison image, and graying the clothing comparison image to obtain a clothing grayscale comparison diagram; The fifth module is used to compare the clothing grayscale comparison image with the preset clothing grayscale reference image, determine the grayscale difference characteristics between the two, and determine the defects on the clothing based on the performance of the grayscale difference characteristics.

[0013] The present invention discloses a method and system for judging clothing quality based on visual data analysis, and relates to the technical field of clothing production line monitoring. Specifically, it discloses that contour edge recognition and part marking are then performed, and the contour of clothing and internal detail edges are screened out using grayscale features, and each part is marked; then a preliminary quality assessment is performed, and the quality of clothing is preliminarily judged by analyzing edge shape, grayscale features, etc.; if the assessment result does not meet the standard, a quality alarm is triggered, and the alarm clothing is accurately photographed to obtain a comparison image; finally, defect comparison and confirmation are performed, and the comparison image is compared with a preset grayscale reference image to determine the grayscale difference characteristics, so as to accurately judge the defect type and severity. The above scheme realizes the automation, efficiency and precision of clothing quality detection, effectively solves the problems of low efficiency and large influence of subjective judgment in traditional manual quality inspection methods, and improves the accuracy and consistency of clothing quality detection.

[0014] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a method step diagram of a clothing quality judgment method based on visual data analysis disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0017] The following will be combined with the accompanying drawings and specific embodiments to clearly and completely describe the technical solution of the present invention. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art in this field can make some non-essential improvements and adjustments based on the content of the present invention described below. In the present invention, unless otherwise clearly specified and limited, the technical terms used in the present invention should be the common meanings understood by the technical personnel described in the present invention.

[0018] Example:

[0019] See also Figure 1 The present invention discloses a method for judging clothing quality based on visual data analysis, comprising: Step S100, lay the clothing on the shooting background board, and use the shooting module to shoot the clothing on the shooting background board to obtain a clothing surface image, pre-process the clothing surface image, and use edge detection technology to determine several edges on the clothing in the clothing surface image.

[0020] This step aims to obtain the surface image of the clothing and perform preliminary processing on it for subsequent analysis. First, lay the clothing flat on the shooting background board to ensure that the clothing is flat and wrinkle-free so as to accurately capture its shape and details. Then, use a shooting module (such as a high-definition camera) to shoot the clothing to obtain the surface image of the clothing. Next, preprocess the image, including denoising, contrast enhancement and other operations to improve the image quality, and use edge detection technology to identify edge information in the image.

[0021] For example, suppose the background is pure white and the clothing is dark blue jeans. The image obtained by the shooting module may contain some ambient light interference or image noise. In the preprocessing stage, a filtering algorithm is used to remove these noises, and the image contrast is enhanced through histogram equalization to make the outline and details of the jeans clearer. Edge detection technology can identify the edges of jeans, including the outlines of the trouser legs, waistband, pockets and other parts.

[0022] In some embodiments disclosed in the present invention, a method for determining a plurality of edges on a garment in a garment surface image using edge detection technology includes: Step S101, preprocessing the clothing surface image, including removing noise and enhancing contrast, and using an edge detection algorithm to calculate the gradient of each pixel, and determine the edge position point according to the size and direction of the gradient.

[0023] Step S102, connecting a number of edge position points whose adjacent distances are less than or equal to a preset value to obtain a linear edge.

[0024] Step S200, analyze the grayscale features beside each edge, use the grayscale features and the grayscale features of the shooting background plate as the screening conditions, screen out the clothing outline edges, determine the part to which the clothing outline edges belong based on the length and shape of the clothing outline edges and the relationship between adjacent clothing outline edges, and mark the part to which they belong, analyze the distance features between other edges and the clothing outline edges, determine the parts to which other edges belong, record them as inner edges of the clothing, and mark the parts to which they belong.

[0025] This step screens out the contour edge of the clothing by analyzing the grayscale features beside the edge. Since the color difference between the shooting background and the clothing is obvious, the contour edge of the clothing can be identified by comparing the grayscale value beside the edge with the grayscale value of the background. Subsequently, based on the length and shape of the contour edge and the relationship between adjacent contour edges, the various parts of the clothing (such as sleeves, collars, front plackets, etc.) are determined and marked. At the same time, the distance features between other edges and the contour edge are analyzed to determine the detailed edges inside the clothing (such as seams, decorative lines, etc.), and the parts are also marked. Let's continue to take dark blue jeans as an example. By comparing the grayscale value of the edge with the grayscale value of the white background, the contour edge of the jeans can be accurately identified. Further analyzing the shape and relationship of these edges, the contours of the trouser legs, waistbands, pockets and other parts can be determined and marked. At the same time, the seams on the jeans will also be identified as internal edges and marked as corresponding part information.

[0026] In some embodiments disclosed in the present invention, based on the length and shape of the edge of the garment outline and the relationship between adjacent garment outline edges, the method for determining the part to which the edge of the garment outline belongs includes: Step S201, a reference garment outline diagram is set for the garment that needs to be judged for quality, the reference garment outline diagram includes a plurality of reference contour edges, and a reference edge length is set for each reference contour edge.

[0027] This step is the basis of the entire method. It establishes a standard template - the reference garment outline. This template contains the contour edge information of each part of the garment, and each edge has a preset reference edge length. This length is the average or typical value based on a large number of sample statistics, which can represent the general characteristics of the edge of the part. By setting the reference garment outline, a clear benchmark is provided for the subsequent recognition and matching of garment outline edges.

[0028] Step S202, based on the length difference between the contour edge length of each garment contour edge and the reference edge length, all garment contour edges are mapped to corresponding positions on the garment contour map. If there are several garment contour edges whose contour edge lengths all meet the mapping condition for the same reference contour edge, the operation of mapping all garment contour edges to the garment contour map is performed several times to form several contour mapping maps.

[0029] This step utilizes the difference between the actual length of the clothing outline edge and the reference edge length to map the clothing outline edge to the corresponding position on the reference clothing outline diagram. This mapping relationship is established based on the similarity of length, and it is assumed that edges with similar lengths are likely to belong to the same part of the clothing. However, due to the complexity and diversity of the actual clothing outline, there may be multiple clothing outline edges that meet the mapping conditions for the same reference outline edge. In order to solve this problem, step S202 adopts the method of multiple mapping operations, that is, a contour mapping diagram is generated for each possible mapping relationship. Although this increases the amount of calculation, it can more comprehensively consider various possibilities and improve the accuracy of subsequent position determination.

[0030] Step S203, based on the inter-image similarity parameter between the contour mapping image and the reference clothing contour image, the most similar contour mapping image is selected, and based on the mapping relationship between the most similar contour mapping image and the clothing contour image, the location of each clothing contour edge on the most similar contour mapping image is determined.

[0031] This step selects the contour mapping that best matches the actual contour features of the garment by comparing the degree of similarity between each contour mapping and the reference garment contour (i.e., the inter-image similarity parameter). The inter-image similarity parameter is a comprehensive evaluation index, which may include information on the length, shape, direction, and adjacent relationship of the contour edge. By calculating the similarity of this information, the degree of similarity between each contour mapping and the reference garment contour can be obtained. After selecting the most similar contour mapping, the part to which each garment contour edge belongs can be determined based on the mapping relationship between the map and the garment contour. This method makes full use of the overall characteristics and local detail information of the garment contour, and improves the accuracy and reliability of part determination.

[0032] In summary, the above technical steps achieve the goal of determining the part to which the edge of a clothing contour belongs based on the length, shape and adjacent relationship of the edge of the clothing contour by setting a reference clothing contour map, mapping and multiple operations on the edge of the clothing contour, and selecting the most similar contour mapping map and determining the part to which the edge belongs. This method has the advantages of clear principle, simple operation and accurate results, and has broad application prospects in the field of clothing quality inspection.

[0033] In some embodiments disclosed in the present invention, a method for determining an inter-image similarity parameter between a contour map and a reference garment contour map includes: Step S2031, comparing the length difference between each clothing contour edge and the reference contour edge, and determining the first similarity parameter of the clothing contour edge and the reference contour edge based on the length difference.

[0034] Step S2032, analyze the shape matching parameters of the clothing contour edge and the reference contour edge, and based on the shape matching parameters, correct the first shape similarity parameter to obtain the second shape similarity parameter, and combine the second shape similarity parameters of other clothing contour edges beside the clothing contour edge to correct the second shape similarity parameter to obtain the third shape similarity parameter.

[0035] Step S2033, calculating the sum of the third similarity parameters of all clothing contour edges, and identifying it as the inter-image similarity parameter.

[0036] Among them, the expression for calculating similar parameters between graphs is: .

[0037] Among them, the expression for calculating the third shape parameter of the clothing contour edge is: .

[0038] The expression for calculating the second shape parameter is: .

[0039] in, is the shape parameter between the figures, is the third shape parameter corresponding to the edge of the i-th clothing contour, is the number of garment outline edges, is the second similarity parameter of the previous clothing contour edge of the i-th clothing contour edge, is the second similarity parameter of the next clothing contour edge after the i-th clothing contour edge, is the influence adjustment coefficient of the second shape parameter, is the second shape parameter affecting the adjustment constant, To preset the minimum second shape parameter, is the preset standard length difference, is the absolute value of the length difference between the edge of the garment contour and the edge of the reference contour, is the shape matching parameter between the edge of the garment contour and the edge of the reference contour, is the adjustment coefficient of shape matching parameter influence, Adjustment constant for shape fit parameter effects.

[0040] In some embodiments disclosed in the present application, the method for determining the shape matching parameter of the edge of the garment contour and the edge of the reference contour includes: Step S20321, setting two parallel contour lines for the reference contour edge, and setting the two sides of the reference contour edge, and identifying the block between the parallel contour lines as the reference contour edge block; Step S20322, determining the edge length of the garment contour edge falling into the reference contour edge block as a shape matching parameter.

[0041] Step S300, respectively analyzing the shape features of the clothing contour edge and the inner edge of the clothing to obtain a first analysis result, and respectively analyzing the grayscale features of the clothing contour edge and the side of the inner edge of the clothing to obtain a second analysis result, and determining a first quality assessment of the clothing based on the first analysis result and the second analysis result.

[0042] This step preliminarily evaluates the quality of clothing by analyzing the shape characteristics of the clothing outline edge and internal edge and the grayscale characteristics of the side. Specifically, it checks whether the edge is continuous and smooth, whether the shape meets the design requirements, and whether the grayscale characteristics are uniform. These analysis results will be combined to form the first quality assessment of the clothing. In the example of jeans, if discontinuities or jagged defects are detected on the edges of the trouser legs, or abnormal grayscale characteristics at the seams (such as obvious color differences or stains), these will be considered negative factors in the quality assessment. After comprehensively analyzing these factors, it can be preliminarily determined whether the quality of the jeans is qualified.

[0043] In some embodiments disclosed in the present invention, the method of analyzing the shape characteristics of the edge of the garment outline and the inner edge of the garment to obtain the first analysis result includes: Step S301, respectively comparing the garment outline edge and the garment inner edge with respective preset standards, determining the garment outline edge or garment inner edge that does not match, and marking it as a defective edge.

[0044] The method of analyzing the grayscale features of the edge of the clothing outline and the side of the inner edge of the clothing to obtain the second analysis result includes: Step S302, a preset standard clothing grayscale image is set for clothing, and based on the clothing outline edge and the clothing inner edge portion, a standard portion grayscale block for comparison on the standard clothing grayscale image is determined.

[0045] Step S303, grayscale extraction is performed on the edge of the clothing outline and the side of the inner edge of the clothing to obtain the grayscale block of the comparison part, and the grayscale block of the comparison part is compared with the grayscale block of the standard part. If the difference characteristics between the two meet the preset standards, the clothing part corresponding to the grayscale block is determined to be a defective clothing part.

[0046] In some embodiments disclosed in the present invention, a first quality assessment of the garment is determined based on the first analysis result and the second analysis result: Step S304, based on the first analysis result and the second analysis result, defective edges and defective blocks with defects on the clothing are determined, and based on the number of defective edges and defective blocks, a first quality assessment of the clothing is determined.

[0047] Step S400: If the first quality assessment result is less than or equal to the preset value, a quality alarm is issued for the corresponding clothing, the clothing with the quality alarm is accurately laid out at a designated position on the shooting background board, and the direction of the clothing is accurately adjusted. The clothing on the background board is photographed again using the shooting module to obtain a clothing comparison image, and the clothing comparison image is grayscaled to obtain a clothing grayscale comparison diagram.

[0048] If the preliminary quality assessment result does not meet the preset quality standard (i.e. the assessment result is less than or equal to the preset value), the quality alarm mechanism is triggered. At this time, the alarmed clothing will be precisely laid out at the designated position of the shooting background board, and its direction will be adjusted to ensure the consistent shooting angle. Then the clothing will be photographed again using the shooting module to obtain a clearer comparison image. The comparison image is grayed for comparison and analysis with the preset clothing grayscale reference image.

[0049] Step S500, comparing the clothing grayscale comparison image with a preset clothing grayscale reference image, determining the grayscale difference characteristics between the two, and determining the defects on the clothing based on the performance of the grayscale difference characteristics.

[0050] This step compares the grayscale comparison image of the clothing with the preset grayscale reference image of the clothing to determine the grayscale difference characteristics between the two. These difference characteristics will directly reflect the possible defects on the clothing (such as stains, color difference, damage, etc.). Based on the expression form and degree of the grayscale difference characteristics, the type and severity of the defects on the clothing can be accurately judged. In the example of jeans, if there is an obvious grayscale difference between the grayscale comparison image and the reference image in the trouser leg part (such as the reference image is a uniform dark blue and the comparison image is light blue or spotted), it can be judged that there is a color difference or stain defect in the jeans leg. The severity of the defect can also be further evaluated based on the degree of grayscale difference.

[0051] In some embodiments disclosed in the present invention, the method of comparing a clothing grayscale comparison image with a preset clothing grayscale reference image includes: Step S501, a probe point mapping array is set for the clothing grayscale comparison image and the clothing grayscale reference image, respectively, and the probe point mapping array includes a plurality of grayscale probe points, and the grayscale values ​​corresponding to the same grayscale probe point on the clothing grayscale comparison image and the clothing grayscale reference image are extracted, respectively, and recorded as the first grayscale value and the second grayscale value, and the combination of the first grayscale value and the second grayscale value is recorded as a comparison grayscale value group, each comparison grayscale value group corresponds to a grayscale probe point, if the grayscale value difference in the comparison grayscale value group corresponding to each grayscale probe point is greater than or equal to a preset value, then the comparison grayscale value group is identified as an abnormal comparison grayscale value group, and the grayscale probe point is marked as an abnormal grayscale probe point; Step S502, randomly projecting a plurality of scanning blocks on the probe point mapping array, if the number of abnormal grayscale probe points in the same scanning block is greater than or equal to a preset value, marking the scanning block as a defective scanning block; Step S503, mapping the defect scanning block to the clothing grayscale comparison map to show the defects on the clothing.

[0052] In some embodiments disclosed in the present invention, there is also disclosed a clothing quality judgment system based on visual data analysis, comprising: The first module is used to lay the clothing on the shooting background board, and use the shooting module to shoot the clothing on the shooting background board to obtain the clothing surface image, pre-process the clothing surface image, and use the edge detection technology to determine a number of edges on the clothing in the clothing surface image; The second module is used to analyze the grayscale features beside each edge, and use the grayscale features and the grayscale features of the shooting background plate as the screening conditions to screen out the clothing outline edges, determine the parts to which the clothing outline edges belong based on the length and shape of the clothing outline edges and the relationship between the adjacent clothing outline edges, and mark the parts to which they belong, analyze the distance features between other edges and the clothing outline edges, determine the parts to which other edges belong, record them as the inner edges of the clothing, and mark the parts to which they belong; The third module is used to analyze the shape characteristics of the clothing contour edge and the inner edge of the clothing to obtain a first analysis result, and to analyze the grayscale characteristics of the clothing contour edge and the side of the inner edge of the clothing to obtain a second analysis result, and to determine a first quality evaluation of the clothing based on the first analysis result and the second analysis result; The fourth module is used for, if the first quality evaluation result is less than or equal to the preset value, issuing a quality alarm for the corresponding clothing, precisely laying the clothing with the quality alarm on a designated position of the shooting background plate, and precisely adjusting the direction of the clothing, using the shooting module to shoot the clothing on the background plate again to obtain a clothing comparison image, and graying the clothing comparison image to obtain a clothing grayscale comparison diagram; The fifth module is used to compare the clothing grayscale comparison image with the preset clothing grayscale reference image, determine the grayscale difference characteristics between the two, and determine the defects on the clothing based on the performance of the grayscale difference characteristics.

[0053] The present invention discloses a method and system for judging clothing quality based on visual data analysis, and relates to the technical field of clothing production line monitoring. Specifically, it discloses that contour edge recognition and part marking are then performed, and the contour of clothing and internal detail edges are screened out using grayscale features, and each part is marked; then a preliminary quality assessment is performed, and the quality of clothing is preliminarily judged by analyzing edge shape, grayscale features, etc.; if the assessment result does not meet the standard, a quality alarm is triggered, and the alarm clothing is accurately photographed to obtain a comparison image; finally, defect comparison and confirmation are performed, and the comparison image is compared with a preset grayscale reference image to determine the grayscale difference characteristics, so as to accurately judge the defect type and severity. The above scheme realizes the automation, efficiency and precision of clothing quality detection, effectively solves the problems of low efficiency and large influence of subjective judgment in traditional manual quality inspection methods, and improves the accuracy and consistency of clothing quality detection.

[0054] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0055] 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 they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A clothing quality judgment method based on visual data analysis, characterized in that: include: The clothing is laid flat on a shooting background board, and the clothing on the shooting background board is photographed by a shooting module to obtain a clothing surface image, the clothing surface image is preprocessed, and a plurality of edges on the clothing in the clothing surface image are determined by edge detection technology; Analyze the grayscale features beside each edge, use the grayscale features and the grayscale features of the shooting background plate as the screening conditions, screen out the clothing outline edge, determine the part to which the clothing outline edge belongs based on the length and shape of the clothing outline edge and the relationship between adjacent clothing outline edges, and mark the part to which it belongs, analyze the distance features between other edges and the clothing outline edge, determine the part to which other edges belong, record them as the inner edge of the clothing, and mark the part to which they belong; Analyze the shape features of the garment contour edge and the inner edge of the garment to obtain a first analysis result, and analyze the grayscale features of the garment contour edge and the inner edge of the garment to obtain a second analysis result, and determine a first quality assessment of the garment based on the first analysis result and the second analysis result; If the first quality evaluation result is less than or equal to the preset value, a quality alarm is issued for the corresponding clothing, the clothing with the quality alarm is accurately laid out at the designated position of the shooting background plate, and the direction of the clothing is accurately adjusted, and the clothing on the background plate is photographed again by using the shooting module to obtain a clothing comparison image, and the clothing comparison image is grayed to obtain a clothing gray comparison map; The clothing grayscale comparison image is compared with the preset clothing grayscale reference image to determine the grayscale difference characteristics between the two, and based on the performance of the grayscale difference characteristics, the defects on the clothing are determined.

2. A method for judging clothing quality based on visual data analysis according to claim 1, characterized in that: Methods for determining several edges on clothing in clothing surface images using edge detection technology include: Preprocess the clothing surface image, including removing noise and enhancing contrast, and use edge detection algorithm to calculate the gradient of each pixel, and determine the edge position point according to the size and direction of the gradient; Connect several edge positions whose adjacent distances are less than or equal to a preset value to obtain a linear edge.

3. The method for judging clothing quality based on visual data analysis according to claim 1, characterized in that: Based on the length and shape of the edge of the garment outline and the relationship between adjacent garment outline edges, the method for determining the part to which the garment outline edge belongs includes: A reference garment outline diagram is set for the garments that need to be judged for quality. The reference garment outline diagram includes a plurality of reference contour edges, and a reference edge length is set for each reference contour edge. Based on the length difference between the contour edge length of each garment contour edge and the reference edge length, all garment contour edges are mapped to corresponding positions on the garment contour map, and if there are several garment contour edges whose contour edge lengths all satisfy the mapping condition for the same reference contour edge, the operation of mapping all garment contour edges to the garment contour map is performed several times to form several contour mapping maps; Based on the inter-image similarity parameter between the contour mapping image and the reference clothing contour image, the most similar contour mapping image is selected, and based on the mapping relationship between the most similar contour mapping image and the clothing contour image, the location of each clothing contour edge on the most similar contour mapping image is determined.

4. The method for judging clothing quality based on visual data analysis according to claim 3, characterized in that: The method for determining the inter-image similarity parameter between the contour map and the reference garment contour includes: Comparing the length difference between each garment outline edge and the reference outline edge, and determining the first shape similarity parameter of the garment outline edge and the reference outline edge based on the length difference; Analyze the shape matching parameters of the clothing contour edge and the reference contour edge, and based on the shape matching parameters, correct the first shape similarity parameter to obtain the second shape similarity parameter, and combine the second shape similarity parameters of other clothing contour edges beside the clothing contour edge to correct the second shape similarity parameter to obtain the third shape similarity parameter; Calculate the sum of the third similarity parameters of all clothing contour edges and identify it as the inter-image similarity parameter; Among them, the expression for calculating similar parameters between graphs is: ； Among them, the expression for calculating the third shape parameter of the clothing contour edge is: ； The expression for calculating the second shape parameter is: ； in, is the shape parameter between the figures, is the third shape parameter corresponding to the edge of the i-th clothing contour, is the number of garment outline edges, is the second similarity parameter of the previous clothing contour edge of the i-th clothing contour edge, is the second similarity parameter of the next clothing contour edge after the i-th clothing contour edge, is the influence adjustment coefficient of the second shape parameter, is the second shape parameter affecting the adjustment constant, To preset the minimum second shape parameter, is the preset standard length difference, is the absolute value of the length difference between the edge of the garment contour and the edge of the reference contour, is the shape matching parameter between the edge of the garment contour and the edge of the reference contour, is the adjustment coefficient of shape matching parameter influence, Adjustment constant for shape fit parameter effects.

5. The method for judging clothing quality based on visual data analysis according to claim 4, characterized in that: The method for determining the shape matching parameters of the garment contour edge and the reference contour edge includes: Two parallel contour lines are set for the reference contour edge, and the two sides of the reference contour edge are set, and the block between the parallel contour lines is identified as the reference contour edge block; The edge length of the garment contour edge falling into the reference contour edge block is identified as the shape matching parameter.

6. The method for judging clothing quality based on visual data analysis according to claim 1, characterized in that: The method of analyzing the shape characteristics of the edge of the garment outline and the inner edge of the garment to obtain the first analysis result includes: Comparing the garment outline edge and the garment inner edge with respective preset standards, determining the garment outline edge or the garment inner edge that does not match the standard, and marking it as a defective edge; The method of analyzing the grayscale features of the edge of the clothing outline and the side of the inner edge of the clothing to obtain the second analysis result includes: A preset standard clothing grayscale image is set for clothing, and based on the clothing outline edge and the clothing inner edge, a standard part grayscale block for comparison on the standard clothing grayscale image is determined; The grayscale extraction of the edge of the clothing contour and the side of the inner edge of the clothing is performed to obtain the grayscale block of the comparison part, and the grayscale block of the comparison part is compared with the grayscale block of the standard part. If the difference characteristics between the two meet the preset standards, the clothing part corresponding to the grayscale block is identified as the defective clothing part.

7. The method for judging clothing quality based on visual data analysis according to claim 1, characterized in that: Based on the first analysis result and the second analysis result, a first quality assessment of the garment is determined: Based on the first analysis result and the second analysis result, defective edges and defective blocks on the clothing are determined, and based on the number of defective edges and defective blocks, a first quality assessment of the clothing is determined.

8. The method for judging clothing quality based on visual data analysis according to claim 1, characterized in that: The method for comparing the clothing grayscale comparison image with the preset clothing grayscale reference image includes: A probe point mapping array is set for the clothing grayscale comparison image and the clothing grayscale reference image, respectively. The probe point mapping array includes a plurality of grayscale probe points. The grayscale values ​​corresponding to the same grayscale probe point on the clothing grayscale comparison image and the clothing grayscale reference image are extracted, respectively, and recorded as the first grayscale value and the second grayscale value, and the combination of the first grayscale value and the second grayscale value is recorded as a comparison grayscale value group. Each comparison grayscale value group corresponds to a grayscale probe point. If the grayscale value difference in the comparison grayscale value group corresponding to each grayscale probe point is greater than or equal to a preset value, the comparison grayscale value group is identified as an abnormal comparison grayscale value group, and the grayscale probe point is marked as an abnormal grayscale probe point. A plurality of scanning blocks are randomly projected on the probe point mapping array. If the number of abnormal grayscale probe points in the same scanning block is greater than or equal to a preset value, the scanning block is marked as a defective scanning block. The defect scanning block is mapped onto the grayscale comparison image of the clothing to show the defects on the clothing.

9. A clothing quality judgment system based on visual data analysis, characterized in that: include: The first module is used to lay the clothing on the shooting background board, and use the shooting module to shoot the clothing on the shooting background board to obtain the clothing surface image, pre-process the clothing surface image, and use the edge detection technology to determine a number of edges on the clothing in the clothing surface image; The second module is used to analyze the grayscale features beside each edge, and use the grayscale features and the grayscale features of the shooting background plate as the screening conditions to screen out the clothing outline edges, determine the parts to which the clothing outline edges belong based on the length and shape of the clothing outline edges and the relationship between the adjacent clothing outline edges, and mark the parts to which they belong, analyze the distance features between other edges and the clothing outline edges, determine the parts to which other edges belong, record them as the inner edges of the clothing, and mark the parts to which they belong; The third module is used to analyze the shape characteristics of the clothing contour edge and the inner edge of the clothing to obtain a first analysis result, and to analyze the grayscale characteristics of the clothing contour edge and the side of the inner edge of the clothing to obtain a second analysis result, and to determine a first quality evaluation of the clothing based on the first analysis result and the second analysis result; The fourth module is used for, if the first quality evaluation result is less than or equal to the preset value, issuing a quality alarm for the corresponding clothing, precisely laying the clothing with the quality alarm on a designated position of the shooting background plate, and precisely adjusting the direction of the clothing, using the shooting module to shoot the clothing on the background plate again to obtain a clothing comparison image, and graying the clothing comparison image to obtain a clothing grayscale comparison diagram; The fifth module is used to compare the clothing grayscale comparison image with the preset clothing grayscale reference image, determine the grayscale difference characteristics between the two, and determine the defects on the clothing based on the performance of the grayscale difference characteristics.

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