Fabric defect detection algorithm based on MFS and SVM

Cuifang Zhao; Yu Chen; Jiacheng Ma

doi:10.1117/12.2513987

29 October 2018 Fabric defect detection algorithm based on MFS and SVM

Cuifang Zhao, Yu Chen, Jiacheng Ma

Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 108360H (2018) https://doi.org/10.1117/12.2513987
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China

Abstract

Fabric defect detection is an important part of quality control in textile producing enterprises. In order to effectively improve the detection probability, the fabric defects detection algorithm based on multifractal spectrum (MFS) and support vector machine (SVM) is proposed in this paper. The detection process is divided into two main parts: feature extraction and classification, including image segmentation, MFS feature extraction, SVM model training, detection classification and classification results. The simulation experiment results show that the algorithm has good performance of detection and classification based on the detection rate and the false alarm rate, and it has a certain robustness and can be applied to the actual generation.

Citation Download Citation

Cuifang Zhao, Yu Chen, and Jiacheng Ma "Fabric defect detection algorithm based on MFS and SVM", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108360H (29 October 2018); https://doi.org/10.1117/12.2513987

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