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hal-00596000, version 1

Reduced graphs for min-cut/max-flow approaches in image segmentation

Nicolas Lermé () 1, 2, Lucas Létocart () 2, Francois Malgouyres () 1

LAGOS'11 : VI Latin-American Algorithms, Graphs, and Optimization Symposium (2011) 6 pages

Résumé : In few years, min-cut/max-flow approach has become a leading method for solving a wide range of problems in computer vision. However, min-cut/max-flow approaches involve the construction of huge graphs which sometimes do not fit in memory. Currently, most of the max-flow algorithms are impracticable to solve such large scale problems. In this paper, we introduce a new strategy for reducing exactly graphs in the image segmentation context. During the creation of the graph, we test if the node is really useful to the max-flow computation. Numerical experiments validate the relevance of this technique to segment large scale images.

  • 1 :  Laboratoire Analyse, Géométrie et Application (LAGA)
  • CNRS : UMR7539 – Université Paris XIII - Paris Nord – Université Paris VIII - Vincennes Saint-Denis
  • 2 :  Laboratoire d'informatique de Paris-nord (LIPN)
  • CNRS : UMR7030 – Université Paris XIII - Paris Nord
  • Domaine : Informatique/Mathématique discrète
 
  • hal-00596000, version 1
  • http://hal.archives-ouvertes.fr/hal-00596000
  • oai:hal.archives-ouvertes.fr:hal-00596000
  • Contributeur : Lucas Létocart <>
  • Soumis le : Jeudi 26 Mai 2011, 10:56:55
  • Dernière modification le : Jeudi 26 Mai 2011, 11:14:13