Research And Implementation Of Fabric Defect Detection

In the production process of textile industry products,fabric defect detection is the most important part of quality control,which is throughout the whole production process.Defects will affect the appearance of the fabric,severely reduce the quality of textile products,and reduce the product price.Therefore,it is very important to reduce the fabric defects for textile production.At present,many textile enterprises in our country still rely on manpower to detect fabric defects.On the whole,the manual detection method can not only achieve strict control of product quality,but also has a large error.With the development of machine vision technology and image processing technology in recent years,more and more enterprises have introduced the automatic detection of fabric defects into industrial production.A new method for warp knit fabric defect detection based on an optimal Gabor filter is presented.As to a defective fabric image,the texture features of defective regions are different from those of defect-free background.Therefore,the fabric defect detection task resembles the segmentation problem where “unknown” defective textures need to be separated from a “known” defect-free texture.The proposed method consists of two processes: the training and the inspection process.In the training process,the parameters of the 2D-Gabor filter can be tuned by the quantum-behaved particle swarm optimization(QPSO)algorithm to match with the texture features of a defect-free template acquired in prior.In the inspection process,each sample fabric image under inspection is convoluted with the selected optimized Gabor filter.Then a simple thresholding scheme is applied to generate a binary segmented result.Experimental results show that the detection rate of the proposed method can reach 96.67%.It has a good performance of stability and robustness,suitable for industrial production.In order to solve the real-time problem of the fabric defect automatic inspection system,a new method for fabric defect detection based on an elliptical Gabor filter is presented.In this method,the traditional 2D-Gabor filter is added to the elliptic component,which can be tuned to any form of Gabor filter.The single Gabor filter is used to ensure the accuracy of detection,so as to meet the requirement of high real-time in industrial production.The experimental results show that the method can meet the requirements of real-time detection of weaving speed below 3m/min.In order to apply the research method to the practical industrial production,this paper has realized a set of an on-line inspection system for the textile defects.Foreign advanced automatic fabric defect detection system has been quite perfect,but it is not widely used because of its high price.There have been some test prototypes in China,but few mature products have been put into practical industrial production.This paper will introduce several modules,which are the system requirements analysis,the overall system design and system testing and experimental analysis.It is hoped that the system implemented in this paper can broaden the train of thought for the research and development of such products.