A novel texture image segmentation method is proposed to segment the wire rope in complex background. Firstly, the Local Binary Pattern (LBP) operator is used to extract local texture feature histogram of sub windows in an image. Then, these histograms are measured statistically by the first-order entropy and second-order entropy to reduce the dimension of LBP characteristic. At the same time, edge density is combined to describe the texture feature. Based on the three features, the Fuzzy C-Mean clustering algorithm is adopted to realize non-supervised texture images segmentation. In the experiment, the results of texture image segmentation by the proposed method are compared with the results of Gray Level Co-occurrence Matrix (GLCM) and typical LBP operator respectively. The results show that the proposed method can realize wire rope image segmentation effectively, and its performance is batter than the GLCM’s and LBP’s.