Handbook of pattern recognition & computer vision
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time vision-based system for textile fabric inspection
Real-Time Imaging
Robust Defect Segmentation in Woven Fabrics
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Leather inspection based on wavelets
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Defect detection in textured materials using optimized filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A flexible visual inspection system based on neural networks
International Journal of Systems Science - Innovative Production Machines and Systems, Guest Editors: Duc-Truong Pham, Anthony Soroka and Eldaw Eldukhri
Detection of Cracks and Corrosion for Automated Vessels Visual Inspection
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Intelligent real-time fabric defect detection
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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This paper presents a new contribution for the problem of automatic visual inspection. New methods for determining threshold values for fabric defect detection using feedforward neural networks are proposed. Neural networks are one of the fastest most flexible classification systems in use. Their implementation in defect detection, where a clear classification is needed, requires thresholding the output. Two methods are proposed for threshold selection, statistical analysis of the NN output and confusion matrix based optimization. Experimental results obtained from the real fabric defects, for the two approaches proposed in this paper, have confirmed their usefulness.