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An Algorithm for Binary Image Segmentation Using Polygonal Markov Fields

  • Rafał Kluszczyński
  • Marie-Colette van Lieshout
  • Tomasz Schreiber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

We present a novel algorithm for binary image segmentation based on polygonal Markov fields. We recall and adapt the dynamic representation of these fields, and formulate image segmentation as a statistical estimation problem for a Gibbsian modification of an underlying polygonal Markov field. We discuss briefly the choice of Hamiltonian, and develop Monte Carlo techniques for finding the optimal partition of the image. The approach is illustrated by a range of examples.

Keywords

Image Segmentation Image Domain Statistical Estimation Problem Total Edge Length Homogeneous Poisson Point Process 
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 2005

Authors and Affiliations

  • Rafał Kluszczyński
    • 1
  • Marie-Colette van Lieshout
    • 2
  • Tomasz Schreiber
    • 1
  1. 1.Nicolaus Copernicus UniversityToruńPoland
  2. 2.CWIAmsterdamThe Netherlands

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