Adaptive Detection Method of Textile Defects Based on Spectrum Analysis

Abstract

The invention relates to the field of textile technology, in particular to an adaptive detection method for textile defects based on frequency spectrum analysis. The method includes: collecting a surface image of a textile, obtaining a grayscale image and a frequency spectrum of the surface image; and generating different filter templates for the frequency spectrum; Using the filter templates to obtain multiple second grayscale images; calculate the offset degree of the edge curve in the edge image according to the coordinates of the pixel points in the edge image of the second grayscale image, and obtain according to the shortest distance between every two edge curves The density of the edge image; get the edge effect of each second grayscale image according to the degree of offset and density and the area ratio of the edge; get the weakening effect of each filter template according to the edge effect; select the filter template with the largest weakening effect The corresponding second grayscale image is used as the detection image, and the defect position of the detection image is determined. The embodiment of the present invention can complete the self-adaptive selection of the filter template and improve the accuracy of textile defect detection.

Description

technical field [0001] The invention relates to the technical field of textiles, in particular to an adaptive detection method for textile defects based on frequency spectrum analysis. Background technique [0002] In the production process of textiles, it is necessary to use the cloth inspection machine to detect the defects of the final textile products. When many cloth inspection machines detect defects, operators need to observe visually under sufficient light sources to find defects such as surface defects and color differences. The machine automatically completes the length recording and package finishing work. In this case, the detection speed of textile defects is low, and the subjectivity of the inspectors has a great influence on the detection results, and it is easy to miss inspection; the cloth inspection machine with good performance is equipped with electronic defect inspection The device uses image segmentation or neural network to identify defect parts, and t...

AI Technical Summary

Problems solved by technology

[0002] In the production process of textiles, it is necessary to use the cloth inspection machine to detect the defects of the final textile products. When many cloth inspection machines detect defects, operators need to observe visually under sufficient light sources to find defects such as surface defects and color differences. The machine automatically completes the length recording and package finishing work. In this case, the detection speed of textile defects is low, and the subjectivity of the inspectors has a great influence on the detection results, and it is easy to miss inspection; the cloth inspection machine with good performance is equipped with electronic defect inspection device, through image segmentation or using neural network to identify defect parts, and textiles often have a lot of texture background features, which may lead to inaccurate defect detection results

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