Combinatorial Pyramids and Discrete Geometry for Energy-Minimizing Segmentation

  • Martin Braure de Calignon
  • Luc Brun
  • Jacques-Olivier Lachaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4292)


This paper defines the basis of a new hierarchical segmentation framework based on an energy minimization scheme. This new framework is based on two formal tools. First, a combinatorial pyramid encodes efficiently a hierarchy of partitions. Secondly, discrete geometric estimators measure precisely some important geometric parameters of the regions. These measures combined with photometrical and topological features of the partition allow to design energy terms based on discrete measures. Our segmentation framework exploits these energies to build a pyramid of image partitions with a minimization scheme. Some experiments illustrating our framework are shown and discussed.


Image Energy Initial Partition Maximal Segment Hierarchical Segmentation Digital Curve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Martin Braure de Calignon
    • 1
  • Luc Brun
    • 2
  • Jacques-Olivier Lachaud
    • 1
  1. 1.LaBRI CNRS UMR 5800Université Bordeaux 1
  2. 2.GreyC CNRS UMR 6072Équipe Image – ENSICAEN

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