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Generalized fast marching method: applications to image segmentation.
- Source :
-
Numerical Algorithms . Jul2008, Vol. 48 Issue 1-3, p189-211. 23p. - Publication Year :
- 2008
-
Abstract
- Abstract  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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *IMAGE processing
*ALGORITHMS
*EXTENSION (Logic)
*MATHEMATICS
Subjects
Details
- Language :
- English
- ISSN :
- 10171398
- Volume :
- 48
- Issue :
- 1-3
- Database :
- Academic Search Index
- Journal :
- Numerical Algorithms
- Publication Type :
- Academic Journal
- Accession number :
- 33054242
- Full Text :
- https://doi.org/10.1007/s11075-008-9183-x