Online automatic detection method of fabric defects based on machine vision and device thereof

Abstract

The invention relates to an online automatic detection method of fabric defects based on machine vision and a device thereof, wherein the clear and integral standard fabric images without the defects of the fabric are shot on a batching and burling machine as a standard image template by utilizing an industrial camera in order to solve the problems of great labor intensity and poor detection quality of the traditional manual detection method; the corresponding characteristic parameters are extracted and stored into a computer; the range of the fabric defect detection characteristic parameters is set according to the requirements of users; the fabric images which are shot in real time are transmitted to the computer to be compared with the standard image template by utilizing the industrial camera and compared with the standard characteristic parameters; if the fabric characteristic parameters are not in conformity with the set requirements, the alarm is started by detection software; the defects are analyzed; and the printing of defects labels is executed. The invention has the advantages of high detection accuracy and high speed; and the labor intensity is greatly reduced.

Description

technical field [0001] The invention relates to the technical field of on-line detection by using machine vision and image processing technology, and mainly relates to a method and a device for on-line detection of fabric defects by using a machine vision system on the spot of finished cloth rolls. Background technique [0002] For a long time, artificial backlight detection or mechanical light detection has been basically used for fabric defect detection, that is, inspectors judge defects by naked eye observation and hand touch according to their own experience by the north window without glare or under fluorescent lighting conditions. Individuals' knowledge of fabric defects and their own experience determine the fabric defects and their types, and then evaluate the fabric grade according to the fabric scoring and rating standards, and give the fabric deduction and evaluation results. However, this method has many disadvantages. First, manual inspection seriously reduces t...

AI Technical Summary

Problems solved by technology

However, the defects of printing and dyeing are only a small part of the total defects of the fabric, and most of the defects are still produced in the weaving process. In order to reduce the cost of quality inspection in the textile industry, improve the quality of inspection, and improve the market competitiveness of products, it is urgent to develop fast and accurate On-line automatic detection system for fabric defects

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