Abstract:Fabric defect characteristic curves of the wavelet coefficients are vulnerable to periodic noise in all layers. It cannot effectively extract features and locate defects area. This paper proposed a method of feature extraction and defect segmentation based on the parameters of entropy, energy, variance curve of difference coefficient after wavelet transform. Firstly, it subtracts the horizontal and vertical high-frequency decomposition coefficients with the smoothing coefficients after wavelet transform, removes the periodic noise, extracts maximum, mean and deviation parameters from the curve difference horizontal and vertical coefficient. Then, it uses support vector machine to classify the extracted features. Simulation results show that the method can effectively locate and segement fabric defect region, and the recognition rate increased by 4.17% compared with the features extracted by wavelet coefficients.