Texture segmentation method based on permutation entropy and gray feature
基于排列组合熵和灰度特征的纹理分割

A method for texture segmentation was presented. According to a feature vector which was made up of the permutation entropies calculated in many different directions, gray average and gray deviation, the method made the texture segmentation by fuzzy c-means algorithm. The experiment results show that the method has a good performance on segmenting images with textures distributed uniformly. On the premise of keeping high precision in texture segmentation, the method reduces the computational complexity, and has the ablility of robustness and noise resistance.