Texture Image Segmentation Based on Description Complexity

From fractal simulation theory, texture images can be reproduced by some texture sets through a nonlinear plural dynamical system. This paper generalizes the KC complexity measure, which is often used in analyzing the complexity of one-dimension time sequence into two-dimension image. The tests prove that the complexity description based on the KC complexity measure is effective. An improved measure method based on the spatial redundancy, is proposed to reduce the sensitivity to noises and to improve the robustness. Comparing with other usual algorithms of texture segmentation, the proposed algorithm has the advantages of less computation and better segmentation performance.