Global Minimum for Active Contour Models : A Minimal Path approachLAURENT

A new boundary detection approach for shape modeling is presented. It detects the global minimum of an active contour model's energy between two points. Initialization is made easier and the curve is not trapped at a local minimum by spurious edges. We modify the \snake" energy by including the internal regularization term in the external potential term. Our method is based on nding a path of minimal length in a Riemannian metric. We then make use of a new eecient numerical method to nd this shortest path. It is shown that the proposed energy, though based only on a potential integrated along the curve, imposes a regularization eeect like snakes. We explore the relation between the maximumcurvature along the resulting contour and the potential generated from the image. The method is capable to close contours, given only one point on the objects' boundary by using a topology{based saddle search routine. We show examples of our method applied to real aerial and medical images.