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Image Segmentation Using A New Scalar Texture Descriptor based on Extended Structure Tensor

The extend structure tensor (EST) is a valuable descriptor for the texture feature of image. However, EST is highly dimensional data which would bring more computational complexity and local minimum in some image. Traditional dimension reduction approaches for EST may not full use of the inherent characteristics of image. In order to solve this problem, a new scalar texture descriptor based on invariant of the EST is presented in this paper. The scalar texture descriptor is composed of the eigenvalues of EST, and used the relationship between the eigenvalues and the element of the EST to avoid direct the computation . Then the scalar texture descriptor is embedded into the segmentation model we proposed which utilizes both global and local image information. The fast energy minimization algorithm instead of the level set method is applied to solve the model. Finally, the experiments on some synthetic and real images are show the efficiency and robustness of the our model.