A feasible approach fog the recognition of silk fabric defects based on wavelet transform and SOM neural network is proposed in this paper, the indispensable processes of which are defect images denoising and enhancement, image edge detection, feature extraction and defects identification. Both geometrical and textural feature panuneters are extracted from the edge image and the enhanced defect image, and utifize SOM neural network to recognize the common defects which silk fabrics have, including warp- lacking, weft-lacking, double weft, loom bars, oll-stalin. Experimental results show the advantages with high identification correctness and high inspection speed.