Fabric Defect Detection Based on Pattern Template Correction

Xingzhi Chang, Chengxi Gu, Jiuzhen Liang and Xin Xu

Mathematical Problems in Engineering, 2018, vol. 2018, 1-17

Abstract:

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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3709821

DOI: 10.1155/2018/3709821

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