Abstract. This paper introduces a new color image segmentation framework that unifies contour deformation and
region-based segmentation. Instead of deforming a single or multiple contours, typically used with classical deformable
contour methods, the proposed framework deforms a single planar net that represents
the contours of all the objects in the image. The net consists of a group of vertices connected by edges
without crossing each other. The connected edges form polygons that represent the segmented regions
boundaries. During the deformation process, the algorithm changes the location and the number of vertices as well as the
number of polygons to enhance the segmentation fit. The deformation forces for each
polygon are generated based upon the average color of the region and the color of the pixels surrounding
it. The algorithm is completely autonomous and does not require any user interference, training or preknowledge about the
image contents. The experimental results demonstrate the capability of the algorithm to segment color images from arbitrary
sources within reasonable time. Furthermore, the compact
mathematical representation of the resulting boundaries could be of value for further image analysis.