FReBIR: An image retrieval system based on fuzzy region matching

  • Authors:
  • Sylvie Philipp-Foliguet;Julien Gony;Philippe-Henri Gosselin

  • Affiliations:
  • Equipes Traitement des Images et du Signal, CNRS/ENSEA/UCP, 6 av. du Ponceau, 95014 Cergy Cedex, France;Equipes Traitement des Images et du Signal, CNRS/ENSEA/UCP, 6 av. du Ponceau, 95014 Cergy Cedex, France;Equipes Traitement des Images et du Signal, CNRS/ENSEA/UCP, 6 av. du Ponceau, 95014 Cergy Cedex, France

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2009

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Abstract

In this paper, we present a method of image indexing and retrieval which takes into account the relative positions of the regions within the image. Indexing is based on a segmentation of the image into fuzzy regions; we propose an algorithm which produces a fuzzy segmentation. The image retrieval is based on inexact graph matching, taking into account both the similarity between regions and the spatial relation between them. We propose, on one hand a solution to reduce the combinatorial complexity of the graph matching, and on the other hand, a measure of similarity between graphs allowing the result images ranking. A relevance feedback process based on region classifiers allows then a good generalization to a large variety of the regions. The method is adapted to partial queries, aiming for example at retrieving images containing a specific type of object. Applications may be of two types, firstly an on-line search from a partial query, with a relevance feedback aiming at interactively leading the search, and secondly an off-line learning of categories from a set of examples of the object. The name of the system is FReBIR for Fuzzy Region-Based Image Retrieval.