Sciweavers

Share
NA
2008

Generalized fast marching method: applications to image segmentation

10 years 1 months ago
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.
Nicolas Forcadel, Carole Le Guyader, Christian Gou
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where NA
Authors Nicolas Forcadel, Carole Le Guyader, Christian Gout
Comments (0)
books