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Mathematical Problems in Engineering
Volume 2018, Article ID 3709821, 17 pages
Research Article

Fabric Defect Detection Based on Pattern Template Correction

1Open Lab of Industrial Cloud for Intelligent Manufacturing, Changzhou College of Information Technology, Changzhou, China
2Changzhou Key Laboratory of Large Plastic Parts Intelligence Manufacturing, Changzhou, China
3School of Information Science and Engineering, Changzhou University, Changzhou, China

Correspondence should be addressed to Jiuzhen Liang; nc.ude.uzcc@gnailzj

Received 11 December 2017; Accepted 11 February 2018; Published 22 March 2018

Academic Editor: Ivan Giorgio

Copyright © 2018 Xingzhi Chang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a novel template-based correction (TC) method for the defect detection on images with periodic structures. In this method, a fabric image is segmented into lattices according to variation regularity, and correction is applied to reduce the effect of misalignment among lattices. Also, defect-free lattices are chosen for establishing an average template as a uniform reference. Furthermore, the defect detection procedure is composed of two steps, namely, defective lattices locating and defect shape outlining. Defective lattices locating is based on classification for defect-free and defective patterns, which involves an improved E-V method with template-based correction and centralized processing, while defect shape outlining provides pixel-level results by threshold segmentation. In this paper we also present some experiments on fabric defect detection. Experimental results show that the proposed method is effective.