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Using 2D Topological Map Information in a Markovian Image Segmentation

  • Guillaume Damiand
  • Olivier Alata
  • Camille Bihoreau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2886)

Abstract

Topological map is a mathematical model of labeled image representation which contains both topological and geometrical information. In this work, we use this model to improve a Markovian segmentation algorithm. Image segmentation methods based on Markovian assumption consist in optimizing a Gibbs energy function. This energy function can be given by a sum of potentials which could be based on the shape or the size of a region, the number of adjacencies,...and can be computed by using topological map. In this work we propose the integration of a new potential: the global linearity of the boundaries, and show how this potential can be extracted from the topological map. Moreover, to decrease the complexity of our algorithm, we propose a local modification of the topological map in order to avoid the reconstruction of the entire structure.

Keywords

Markovian segmentation topological maps region segmentation boundaries linearity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Guillaume Damiand
    • 1
  • Olivier Alata
    • 1
  • Camille Bihoreau
    • 1
  1. 1.IRCOM-SIC, UMR-CNRS 6615Futuroscope Chasseneuil CedexFrance

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