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arXiv 2012.058002020-12-09cs.CVeess.IV

Sylvester Matrix Based Similarity Estimation Method for Automation of Defect Detection in Textile Fabrics

University of Peradeniya（佩拉德尼亚大学）

R. M. L. N. Kumari, G. A. C. T. Bandara, Maheshi B. Dissanayake

备注：: Journal of Sensors, Hindawi
发表信息：: Journal of Sensors,Volume 2021, Article ID 6625421
DOI：: 10.1155/2021/6625421

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英文摘要：

Fabric defect detection is a crucial quality control step in the textile manufacturing industry. In this article, machine vision system based on the Sylvester Matrix Based Similarity Method (SMBSM) is proposed to automate the defect detection process. The algorithm involves six phases, namely resolution matching, image enhancement using Histogram Specification and Median-Mean Based Sub-Image-Clipped Histogram Equalization, image registration through alignment and hysteresis process, image subtraction, edge detection, and fault detection by means of the rank of the Sylvester matrix. The experimental results demonstrate that the proposed method is robust and yields an accuracy of 93.4%, precision of 95.8%, with 2275 ms computational speed.

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