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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Intelligent Real-Time Fabric Defect Detection
verfasst von : Hugo Peres Castilho, Paulo Jorge Sequeira Gonçalves, João Rogério Caldas Pinto, António Limas Serafim
Erschienen in: Image Analysis and Recognition
Verlag: Springer Berlin Heidelberg
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This paper presents real-time fabric defect detection based in intelligent techniques. Neural networks (NN), fuzzy modeling (FM) based on product-space fuzzy clustering and adaptive network based fuzzy inference system (ANFIS) were used to obtain a clearly classification for defect detection. Their implementation requires thresholding its output, and based in previous studies a confusion matrix based optimization is used to obtain the threshold. Experimental results for real fabric defect detection were obtained from the experimental apparatus presented in the paper, that showed the usefulness of the three intelligent techniques, although the NN has a faster performance. Online implementation of the algorithms showed they can be easily implemented with commonly available resources and may be adapted to industrial applications without great effort.