Characterization and classification of fabric defects using discrete cosine transformation and artificial neural network

Abstract

This paper reports how images of woven fabric defects are gathered using charge coupled device imaging technique and digitized. Discrete cosine transformation (DCT) technique is adopted to characterize the defects and back propagation algorithm based artificial neural network is used to classify the various fabric defects. DCT technique is found to give outstanding results for classification of fabric defects. The comparatively high prediction error in one or two cases may be due to the insufficient information about the particular defect from the coefficients of that defect.