文章基本信息

标题：Automatic Defect Detection Algorithm for Woven Fabric using Artificial Neural Network Techniques
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作者：Dr. G. M. Nasira ; P.Banumathi
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：1
出版社：S&S Publications
摘要：Textile industry is one of the main sources of revenue - generated industry. The price of fabrics is severely affected by the defects of fabrics that represent a major threat to the textile industry. A very small percentage of defects are detected by the man ual inspection even with highly trained inspectors which is time consuming and not accurate enough. An automatic defect detection system can increase the defect detection percentage; it reduces the fabrication cost and economically profitable when we consi der the labour cost and associated benefits. In this paper we have proposed a method to detect the defects in woven fabric. The images are acquired, pre - processed and normalized then a structural feature is extracted. The Artificial Neural Network is used as defect identification model. The extracted features are given as input to the artificial neural network, it identifies the defect. The proposed method compare with relevant recently reported works and shows a better performance which is to be very promi
关键词：Artificial Neural Networks(ANN); Back Propagation Algorithm; Defect Identification; Feature Extraction; Image Processing