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.
Chang, X., Gu, C., Liang, J., & Xu, X. (2018). Fabric Defect Detection Based on Pattern Template Correction. Mathematical Problems in Engineering, 2018, 1–17. https://doi.org/10.1155/2018/3709821