Active Contour Model Combined Unsupervised Texture Segmentation

By defining three texture parameters,the definition parameter,detail signal energy parameter and edge signal energy parameter,we analyze the texture feature of the original image,then we obtain the feature energy map of the image.Based on the feature energy map,we segment the image by applying a simplified Mumford-Shah based active contour model.This model can well deal with the problems such as blurry or default edges,and at the same time denoise the image.The model is with the solution by level set method,therefore the topology of the evolving curve can be changed.In comparison with the traditional texture analysis methods,the proposed texture feature analysis method can better reveal the complicated texture signal features in the image.Synthesized textured images and natural textured images were used for testing,and the experimental results show that our method can effectively segment the textured images.