Variational image segmentation by unifying region and boundary information

This paper presents a novel variational image segmentation technique that unifies both geodesic active contours and geodesic active regions. The originality of the method is the automatic and dynamic global weighting of the respective local equations of motion. A new stopping function for the geodesic active contours is also introduced, which proves to have a better behavior in the vicinity of the object boundaries. Instead of minimizing the standard energy functional, we use a normalized version, which strongly reduces the shortening effect, improving thus the coupling with the region model. Results and method effectiveness are shown on real and medical images.