Algorithm for Image Segmentation Based on Anisotropic Diffusion

A new algorithm for image segmentation based on anisotropic diffusion is proposed. The existing regularity method about anisotropic diffusion is introduced. The diffusion equation is decomposed as a second order equation about surface differential curvature according to the theory of conformal mapping in differential geometry. The regularity condition of the decomposed equation is discussed to guarantee a stable solution. Then, the diffusion coefficients in the decomposed equation are analyzed to get a further control on the anisotropic diffusion. An initial segmentation is generated with a watershed transform based on the mathematical morphology. The final segmentation is reached by eliminating the over-segmentation of initial regions. An energy minimum criterion is applied to guide the region merging in nonlinear scale space. The experiment shows that the proposed algorithm provides recognition and understanding processing with improved input.