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Fabric Defect Detection Based on Pattern Template Correction

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  • Xingzhi Chang
  • Chengxi Gu
  • Jiuzhen Liang
  • Xin Xu

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.

Suggested Citation

  • Xingzhi Chang & Chengxi Gu & Jiuzhen Liang & Xin Xu, 2018. "Fabric Defect Detection Based on Pattern Template Correction," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-17, March.
  • Handle: RePEc:hin:jnlmpe:3709821
    DOI: 10.1155/2018/3709821
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