Affine Coordinate-Based Parametrized Active Contours for 2D and 3D Image Segmentation.

In this paper, we present a new framework for image segmentation based on parametrized active contours. The contour and the points of the image space are parametrized using a set of reduced control points that form a closed polygon in two dimensional problems and a closed surface in three dimensional problems. The active contour evolves by moving the control points. The parametrization, that uses mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. The proposed framework allows to easily formulate region-based energies as the one proposed by Chan and Vese in both two and three dimensional segmentation problems. We show the usefulness of our approach with several experiments.