id: 05900433
dt: a
an: 05900433
au: Damiand, Guillaume; Dupas, Alexandre; Lachaud, Jacques-Olivier
ti: Combining topological maps, multi-label simple points, and minimum-length
    polygons for efficient digital partition model.
so: Aggarwal, Jake K. (ed.) et al., Combinatorial image analysis. 14th
    international workshop, IWCIA 2011, Madrid, Spain, May 23‒25, 2011.
    Proceedings. Berlin: Springer (ISBN 978-3-642-21072-3/pbk). Lecture
    Notes in Computer Science 6636, 56-69 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: Topological Map; ML-Simple Point; Minimum-Length Polygon; Deformable Model;
    Interpixel Boundaries; Multi-Label Image
ci: 
li: doi:10.1007/978-3-642-21073-0_8
ab: Summary: 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.
rv: