Effective Region-based Relevance Feedback for Interactive Content-based Image Retrieval

  • Walid Barhoumi
  • Abir Gallas
  • Ezzeddine Zagrouba
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 226)

Abstract

This paper proposes an effective framework for interactive region-based image retrieval. By utilizing fuzzy coarse segmentation and the graph structure for representing each image, the retrieval process was performed by measuring the image similarity according to the graph similarity. To assess the similarity between two graphs, fuzzy inter relations among regions feature vectors and spatial dispositions as well as fuzzy regions weights are explored. A region-based relevance feedback scheme was also incorporated into the retrieval process, by updating the importance of query image regions based on the user feedbacks, leading to a further performance improvement. Experimental study proves that the proposed region-based relevance feedback mechanism tailors the system semantic behavior relatively to each user personal preferences through the accumulation of the useful semantic information from the feedback information.

Keywords

Image Retrieval Query Image Relevance Feedback Salient Region Relevant Image 
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 2009

Authors and Affiliations

  • Walid Barhoumi
    • 1
  • Abir Gallas
    • 1
  • Ezzeddine Zagrouba
    • 1
  1. 1.Institut Supérieur d’InformatiqueEquipe de Recherche “Systèmes Intelligents en Imagerie et Vision Artificielle” (SIIVA)ArianaTunisia

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