In Combinatorial Image Analysis, 2011, Springer Berlin / Heidelberg
10.1007/978-3-642-21073-0_8
Deformable models have shown great potential for image segmentation. They include discrete models whose combinatorial formulation leads to efficient and sometimes optimal minimization algorithms. In this paper, we propose a new discrete framework to deform any partition while preserving its topology. We show how to combine the use of multi-label simple points, topological maps and minimum-length polygons in order to implement an efficient digital deformable partition model. Our experimental results illustrate the potential of our framework for segmenting images, since it allows the mixing of region-based, contour-based and regularization energies, while keeping the overall image structure.
@inproceedings{DamiandAl2011a,
author = {Damiand, G. and Dupas, A. and Lachaud, J.-O.},
affiliation = {Université de Lyon, CNRS, LIRIS, UMR5205, 69622 France},
title = {Combining Topological Maps, Multi-Label Simple Points, and Minimum-Length Polygons for Efficient Digital Partition Model},
booktitle = {Combinatorial Image Analysis},
series = {Lecture Notes in Computer Science},
editor = {Aggarwal, Jake and Barneva, Reneta and Brimkov, Valentin and Koroutchev, Kostadin and Korutcheva, Elka},
publisher = {Springer Berlin / Heidelberg},
isbn = {},
pages = {56-69},
volume = {6636},
url = {http://dx.doi.org/10.1007/978-3-642-21073-0_8},
note = {10.1007/978-3-642-21073-0_8},
year = {2011}
}