Volume 8, Issue 1
Defect Detection on Printed Fabrics Via Gabor Filter and Regular Band

Xuejuan Kang, Panpan Yang & Junfeng Jing

Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 195-206.

Published online: 2015-08

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  • Abstract

Two methods are proposed in this paper to inspect printed fabrics. One method is to apply a genetic algorithm to select parameters of optimal Gabor filter. Optimal Gabor filter can reduce the noise information of printed fabrics, which can achieve defect detection of printed fabrics. The other is in utilizing distance matching function to determine the unit of printed fabrics. Extracting features on a moving unit of printed fabrics can realize defect segmentation of printed fabrics. Two approaches of defect detection have their own advantages. Detecting method with Gabor filter using genetic algorithm has perfect detection results of random printed fabrics, the other method based on statistical rule can receive better defect detection results of regular printed fabrics. Both methods can be realized in practice and detection time of proposed methods can occupy little in total detection time.

  • Keywords

Defect Detection Gabor Filter Regular Band Textile Fabrics

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@Article{JFBI-8-195, author = {}, title = {Defect Detection on Printed Fabrics Via Gabor Filter and Regular Band}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2015}, volume = {8}, number = {1}, pages = {195--206}, abstract = {Two methods are proposed in this paper to inspect printed fabrics. One method is to apply a genetic algorithm to select parameters of optimal Gabor filter. Optimal Gabor filter can reduce the noise information of printed fabrics, which can achieve defect detection of printed fabrics. The other is in utilizing distance matching function to determine the unit of printed fabrics. Extracting features on a moving unit of printed fabrics can realize defect segmentation of printed fabrics. Two approaches of defect detection have their own advantages. Detecting method with Gabor filter using genetic algorithm has perfect detection results of random printed fabrics, the other method based on statistical rule can receive better defect detection results of regular printed fabrics. Both methods can be realized in practice and detection time of proposed methods can occupy little in total detection time.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi03201519}, url = {http://global-sci.org/intro/article_detail/jfbi/4699.html} }
TY - JOUR T1 - Defect Detection on Printed Fabrics Via Gabor Filter and Regular Band JO - Journal of Fiber Bioengineering and Informatics VL - 1 SP - 195 EP - 206 PY - 2015 DA - 2015/08 SN - 8 DO - http://doi.org/10.3993/jfbi03201519 UR - https://global-sci.org/intro/article_detail/jfbi/4699.html KW - Defect Detection KW - Gabor Filter KW - Regular Band KW - Textile Fabrics AB - Two methods are proposed in this paper to inspect printed fabrics. One method is to apply a genetic algorithm to select parameters of optimal Gabor filter. Optimal Gabor filter can reduce the noise information of printed fabrics, which can achieve defect detection of printed fabrics. The other is in utilizing distance matching function to determine the unit of printed fabrics. Extracting features on a moving unit of printed fabrics can realize defect segmentation of printed fabrics. Two approaches of defect detection have their own advantages. Detecting method with Gabor filter using genetic algorithm has perfect detection results of random printed fabrics, the other method based on statistical rule can receive better defect detection results of regular printed fabrics. Both methods can be realized in practice and detection time of proposed methods can occupy little in total detection time.
Xuejuan Kang, Panpan Yang & Junfeng Jing. (2019). Defect Detection on Printed Fabrics Via Gabor Filter and Regular Band. Journal of Fiber Bioengineering and Informatics. 8 (1). 195-206. doi:10.3993/jfbi03201519
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