Chan-Vese Segmentation

While many segmentation methods rely heavily in some way on edge detection, the Active Contours Without Edges method by Chan and Vese [7, 9] ignores edges completely. Instead, the method optimally fits a two-phase piecewise constant model to the given image. The segmentation boundary is represented implicitly with a level set function, which allows the segmentation to handle topological changes more easily than explicit snake methods. This article describes the level set formulation of the Chan-Vese model and its numerical solution using a semi-implicit gradient descent. We also discuss the Chan-Sandberg-Vese method [8], a straightforward extension of Chan-Vese for vector-valued images.