Automatic cloth defect point detection and recognition device and method based on machine vision

Abstract

The invention discloses an automatic cloth defect point detection and recognition device and method based on machine vision. The method includes the steps of taking the picture of a piece of defect-point-free cloth through a camera to serve as a standard image, saving the standard image into a computer, extracting the characteristic parameters of the standard image through an image processing method based on the combination of wavelet conversion and a protection method, taking the picture of a piece of to-be-detected cloth in real time through the camera, extracting the characteristic parameters, setting the accuracy range according to the requirements, comparing the to-be-detected image with the standard image and analyzing the to-be-detected image and the standard image, judging whether defect points exist or not according to whether the characteristic parameters of the to-be-detected image are within the accuracy range or not, saving the image with the defect points if the defect points exist, recognizing the defect points in the image containing the defect points through an image processing method based on optimized threshold value segmentation, completing classifying and grading of the defect points, and conducting level evaluation on the whole cloth. The device and the method overcome the defects that traditional manual visual measurement is low in speed and accuracy and high in detection omission rate and false drop rate, the labor intensity of manual defect point classification is lowered, and the device and the method have the advantage of being accurate in grading.

Description

technical field [0001] The invention relates to cloth defect detection technology in the textile industry, in particular to a device and method for automatic detection and identification of cloth defects based on machine vision. Background technique [0002] For a long time, the quality inspection of cloth is usually carried out manually by inspectors, and the inspection results are greatly affected by subjective factors such as the inspector's proficiency, physical condition, workshop environment, etc. This method can easily cause visual fatigue, high labor intensity, and There are disadvantages such as low detection efficiency, high missed detection rate and false detection rate, so it is urgent to develop a fast, efficient and accurate cloth defect automatic detection and identification system to replace manual visual inspection. [0003] Machine vision is the use of machine automation systems instead of human eyes for measurement and judgment. Compared with manual detec...

AI Technical Summary

Problems solved by technology

[0002] For a long time, the quality inspection of cloth is usually carried out manually by inspectors, and the inspection results are greatly affected by subjective factors such as the inspector's proficiency, physical condition, workshop environment, etc. This method can easily cause visual fatigue, high labor intensity, and There are disadvantages such as low detection efficiency, high missed detection rate and false detection rate, so it is urgent to develop a fast, efficient and high-accuracy automatic detection and identification system for cloth defects to replace manual visual inspection

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