Abstract: A method for recognition of surface defects on strip based on wavelet transform and gray level co-occurrence matrix (GLCM) are proposed. Wavelet transform is used to decompose defect image and extract their low frequency sub-band. By constructing gray level co-occurrence matrices in four directions of 0°, 45°, 90°and 135° on low frequency sub-band, four eigenvalues of angular second moment, contrast, entropy and inverse difference moment are calculated respectively, and obtain 16 eigenvalues, which are input into support vector machine (SVM), complete the recognition of surface defects on strip of 1 800 images in six categories. The overall recognition accuracy is more than 96%. The experimental results show that the combination of wavelet transform and gray level co-occurrence matrix can effectively describe the texture characteristics of surface defects on strip and has a good recognition effect.