Generalized fast marching method: applications to image segmentation
Generalized fast marching method: applications to image segmentation
复制标题
DOI：
10.1007/s11075-008-9183-x
复制
发表时间：
2008-07-01
影响因子：
2.1
通讯作者：
Gout, Christian
中科院分区：
文献类型：
--
作者：
Forcadel, Nicolas;Le Guyader, Carole;Gout, Christian
In this paper, we propose a segmentation method based on the generalized fast marching method (GFMM) developed by Carlini et al. (submitted). The classical fast marching method (FMM) is a very efficient method for front evolution problems with normal velocity (see also Epstein and Gage, The curve shortening flow. In: Chorin, A., Majda, A. (eds.) Wave Motion: Theory, Modelling and Computation, 1997) 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 (Chan and Vese, IEEE Trans Image Process 10(2):266-277, 2001). 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.
