Image Retrieval Using Fuzzy Relevance Feedback and Validation with MPEG-7 Content Descriptors

  • M. Banerjee
  • M. K. Kundu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4815)


Content-Based Image retrieval has emerged as one of the most active research directions in the past few years. In CBIR, selection of desired images from a collection is made by measuring similarities between the extracted features. It is hard to determine the suitable weighting factors of various features for optimal retrieval when multiple features are used. In this paper, we propose a relevance feedback frame work, which evaluates the features, from fuzzy entropy based feature evaluation index (FEI) for optimal retrieval by considering both the relevant as well as irrelevant set of the retrieved images marked by the users. The results obtained using our algorithm have been compared with the agreed upon standards for visual content descriptors of MPEG-7 core experiments.


Content-Based image retrieval fuzzy feature evaluation index invariant moments MPEG-7 feature descriptors 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • M. Banerjee
    • 1
  • M. K. Kundu
    • 1
  1. 1.Machine Intelligence Unit, Center for Soft Computing Research, Indian Statistical Institute, 203, B. T. Road, Kolkata 700 108India

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