Abstract: Owing to numerous kinds of fabric weaves and varied characteristics of fabric surface,it is very difficult to establish a universal fabric defect detection model.In order to solve this problem and realize automatic inspection of fabric,a method for identification of the defects on the fabric by using the double layer neural network and wavelet analysis is proposed.To be specific,the first layer BP neural network is utilized to tell the defects of a normal fabric and acquire its characteristics through repeated training,and then,the twodimensional discrete wavelet transformation based on the image of the defects is conducted,wiping off the inherent characteristics of the fabric and identifying the defects by means of the trained BP neural network.The experiments demonstrated that this method is of high accuracy and high speed,satisfying the elementary requirements of automatic cloth inspection.