Intelligent real-time fabric defect detection

Authors:
Hugo Peres Castilho;Paulo Jorge Sequeira Gonçalves;João Rogério Caldas Pinto;António Limas Serafim3
Affiliations:
Instituto Nacional de Engenharia Tecnologia e Inovação, Estrada do Paço do Lumiar, Lisboa, Portugal;IDMEC/IST, Technical University of Lisbon, Pais, Lisboa and Polytechnical Institute of Castelo Branco, Castelo Branco, Portugal;IDMEC/IST, Technical University of Lisbon, Pais, Lisboa, Portugal;Instituto Nacional de Engenharia Tecnologia e Inovação, Estrada do Paço do Lumiar, Lisboa, Portugal
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

This paper presents real-time fabric defect detection based in intelligent techniques. Neural networks (NN), fuzzy modeling (FM) based on productspace 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.