Active contours and information theory for supervised segmentation on scalar images

In this paper, we present two models for supervised scalar image segmentation based on the active contours and information theory. First we propose to carry out a region competition by optimizing an energy designed to be minimal when the entropy of the inside and outside regions of the evolving active contour are close to those of a reference image. The probability density functions (pdfs) used by this model can be computed in a preprocessing...