Feature purification fusion structure for fabric defect detection
Author:
Funder
science and technology program project of Tianjin
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03066-8.pdf
Reference34 articles.
1. Meier, R., Uhlmann, J., Leuenberger, R.: More than meets the eye-a quality revolution. Textile Month. 34, 36 (1999)
2. Jing, J., Fan, X., Li, P.: Automated fabric defect detection based on multiple Gabor filters and KPCA. Int. J. Multimed. Ubiquitous Eng. 11(6), 93–106 (2016)
3. Qin, W., Wen, H., Li, F.: Fabric defect detection algorithm based on residual energy distribution and Gabor feature fusion. Vis. Comput. (2022). https://doi.org/10.1007/s00371-022-02706-9
4. Karlekar, V. V., Biradar, M. S., Bhangale, K. B.: Fabric defect detection using wavelet filter. In: 2015 International Conference on Computing Communication Control and Automation. IEEE. pp. 712–715 (2015)
5. Zhang, S., Jing, J., Zhang, J., Zhao, J., Li, S.: Draw textured yarn packages hairiness defect detection based on the multi-directional anisotropic gaussian directional derivative. Fibers Polym. 23(13), 3655–3664 (2022)
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