For the problem of complex texture and difficulty in defect detection of mesh fabric. An algorithm based on local binary pattern (LBP) and low rank sparse matrix decomposition for defect detection of mesh fabric is proposed. Firstly, the local binary pattern with equivalent invariant rotation is used to extract the features of the mesh fabric image, and the texture feature matrix is obtained. Then, an appropriate lowrank sparse decomposition model is constructed based on the texture feature matrix. Finally, the significant graph generated by sparse matrix was segmented by OTSU optimal threshold segmentation algorithm, so that the defects of mesh fabric could be detected. Compared with KSVD algorithm, the experimental results show that the average accuracy of the method in this paper is 8994%, the average recall rate is over 9388%, and the total accuracy of classification is over 92%.