Improved random walker interactive image segmentation algorithm for texture image segmentation

In order to improve the accuracy of texture image segmentation, we introduce an improved random walker interactive image segmentation algorithm. With some simple user input, we can achieve accurate segmentation of texture image. Firstly, in this paper, we use gabor energy filters to establishes a texture-based similarity weight function expression. Secondly, we build Laplacian matrix to express the adjacency relation between nodes in an undirected graph. Finally, by solving Dirichlet boundary conditions, a high-quality image segmentation result can be achieved. The final experiments demonstrated that the proposed algorithm more accurately describes the texture image structural information, is more suitable for texture image segmentation.