Abstract: In order to improve the efficiency of leather defect detection, a leather defect detection algorithm based on improved bilateral filtering was proposed. Through constructing machine vision detection platform, different kinds of defects in the finished leather sample image were obtained, sample images were processed with improved bilateral filtering algorithms to make the leather background texture fuzzy and keep its defect edge profile. Then, various kinds of defects of four characteristic parameters were calculated as the input vector, and the automatic identification of least squares support vector machine (SVM) mode was constructed. The results showed that compared with cluster analysis algorithm, threshold segmentation algorithm and wavelet analysis algorithm, the algorithm adopted in this paper could detect various defects of leather more efficiently. The average detection time was 0.83s, and the accuracy of defect detection was 93.3%. The results provide an effective way for real-time leather detection.