Community Detection for Hierarchical Image Segmentation

  • Arnaud Browet
  • P. -A. Absil
  • Paul Van Dooren
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6636)

Abstract

In this paper, we present a new graph-based technique to detect segments or contours of objects in a given picture. Our algorithm is designed as an approximation of the Louvain method that unfolds the community structures in a large graph. Without any a priori knowledge on the input picture, relevant regions are extracted while the optimal definition of a contour, depending on the user or the application, can be tuned using parameters. The communities found are also hierarchical allowing to find subregions inside an object. We present experimental results of our method on real images.

Keywords

Image segmentation community detection modularity optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Arnaud Browet
    • 1
  • P. -A. Absil
    • 1
  • Paul Van Dooren
    • 1
  1. 1.ICTEAM InstituteUniversité catholique de LouvainLouvain-la-NeuveBelgium

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