Digital image processing techniques for automatic textile quality control

作     者：Bennamoun, M. Bodnarova, A. 

作者机构：Space Centre for Satellite Navigation Queensland University of Technology GPO Box 2434 Brisbane QLD 4001 Australia School of Computer Science and Software Engineering University of Western Australia 35 Stirling Highway Crawley WA 6009 Australia 

出 版 物：《Systems Analysis Modelling Simulation》 (Syst Anal Modell Simul)

年 卷 期：2003年第43卷第11期

页      面：1581-1614页

核心收录：

学科分类：07[理学] 070101[理学-基础数学] 0821[工学-纺织科学与工程] 0810[工学-信息与通信工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 070207[理学-光学] 0817[工学-化学工程与技术] 081203[工学-计算机应用技术] 082201[工学-制浆造纸工程] 0835[工学-软件工程] 0803[工学-光学工程] 0822[工学-轻工技术与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学] 

主　　题：Image processing 

摘      要：This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality inspection of textiles suggested a texture analysis approach. Since each texture analysis method presents a different potential for analysis of textured textile images, a large number of standard approaches from this category was examined. By considering their advantages and potential for successful flaw detection performance in homogeneous and jacquard textiles, six standard texture analysis techniques were identified for further investigation. A comprehensive examination and evaluation of these chosen techniques resulted. Normalised cross-correlation and SCLC approaches were identified as suitable candidates for real-time flaw detection in textiles with homogeneous structure. Inspection of jacquard textiles, however, presents a problem of greater complexity, the solution to which has not as yet been documented in the literature. To address this problem, a need for the application of a com-prehensive cojoint spatial-spatial frequency approach was identified. A Gabor filter approach was chosen as a suitable representative of this class of techniques. This research then successfully applied optimised 2-D Gabor filters to the textile flaw detection problem and provided a further support of their suitability for this task. A novel optimised 2-D Gabor algorithm presented in this study is an automatic solution which is adaptable to detect a large variety of textile flaw types, both structural and tonal.