面向织物疵点检测的图像处理技术研究进展

doi:10.13475/j.fzxb.20200702710

Abstract

Abstract:

With the enhancement of product quality requirements in the textile industry and the limitations of traditional defect detection methods, the automatic detection of fabric defects based on image processing technology has seen an rapidly development. Compared with traditional technology, the application of image processing technology improves the processing efficiency and realizes the digitization and intelligent manufacturing of the textile industry. This paper introduces the preprocessing technology of fabric images, and summarizes the mainstream methods of fabric defect detection, including structure-based methods, statistics-based methods, spectrum-based methods, model-based methods and learning-based methods. In addition, it reviews the principles of these methods, and examines their advantages and disadvantages and scope of applications. Besides, the paper introduces the existing finished equipment and compares the advantages and disadvantages of these equipment. Difficulties facing the existing image processing technology in the application of the textile industry are analyzed, and prospects of future development are discussed.

Key words: digital image processing, defect detection, fabric defect, image preprocessing, machine vision

CLC Number:

TP181

LÜ Wentao, LIN Qiqi, ZHONG Jiaying, WANG Chengqun, XU Weiqiang. Research progress of image processing technology for fabric defect detection[J].Journal of Textile Research, 2021, 42(11): 197-206.

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Research progress of image processing technology for fabric defect detection

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