Classifying Textile Faults with a Back-Propagation Neural Network Using Power Spectra

摘要

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. Experimental results show that the system is able to detect and classify nine out of the twelve kinds of defects in its data base.