A real-time system designed to detect and classify textile defects is presented. The system starts with an analysis of the optical Fourier transform of sample textiles. We also use a back-propagation neural network to help detect and classify defects. Exper- imental results show that the system is able to detect and classify nine out of the twelve kinds of defects in its data base.
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