P. Getreuer, “Chan–Vese Segmentation,” Image Processing On Line, 2012. DOI: 10.5201/ipol.2012.g-cv.
Article permalink: http://dx.doi.org/10.5201/ipol.2012.g-cv
@article{getreuer2012chanvese, title = {{Chan--Vese} Segmentation}, author = {Pascal Getreuer}, journal = {Image Processing On Line}, year = {2012}, doi = {10.5201/ipol.2012.g-cv},}See also the original work by Chan and Vese, “Active Contours Without Edges.”
While many segmentation methods rely heavily in some way on edge detection, the “Active Contours Without Edges” method by Chan and Vese 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, a straightforward extension of Chan–Vese for vector-valued images.