Fabric Textile Defect Detection, By Selecting A Suitable Subset Of Wavelet Coefficients, Through Genetic Algorithm

This paper presents a novel approach for defect detection of fabric textile. For this purpose, First, all wavelet coefficients were extracted from an perfect fabric. But an optimal subset of These coefficients can delete main fabric of image and indicate defects of fabric textile. So we used Genetic Algorithm for finding a suitable subset. The evaluation function in GA was Shannon entropy. Finally, it was shown that we can gain better results for defect detection, by using two separable sets of wavelet coefficients for horizontal and vertical defects. This approach, not only increases accuracy of fabric defect detection, but also, decreases computation time