Generalized fast marching method: applications to image segmentation

In this paper, we propose a segmentation method based on the Generalized Fast Marching Method (GFMM) developed by Carlini et al.([6]). The classical Fast Marching Method (FMM) is a very efficient method for front evolution problems with normal velocity (see also [13]) of constant sign. The GFMM is an extension of the FMM and removes this sign constraint by authorizing time-dependent velocity with no restriction on the sign. In our modelling, the velocity is borrowed from the Chan-Vese model for segmentation ([9]). The algorithm is presented and analyzed and some numerical experiments are given, showing in particular that the constraints in the initialization stage can be weakened and that the GFMM offers a powerful and computationally efficient algorithm.

• Type: Journal
• Year: 2008
• Where: NA
• Authors: Nicolas Forcadel, Carole Le Guyader, Christian Gout
• Keywords: Fast Marching Method, NA 2008, Segmentation Method, Velocity