Open Access

Accelerating of Image Retrieval in CBIR System with Relevance Feedback

  • Goran Zajić1Email author,
  • Nenad Kojić1,
  • Vladan Radosavljević2,
  • Maja Rudinac1,
  • Stevan Rudinac3,
  • Nikola Reljin1,
  • Irini Reljin1, 3 and
  • Branimir Reljin3
EURASIP Journal on Advances in Signal Processing20072007:062678

https://doi.org/10.1155/2007/62678

Received: 12 September 2006

Accepted: 29 April 2007

Published: 26 June 2007

Abstract

Content-based image retrieval (CBIR) system with relevance feedback, which uses the algorithm for feature-vector (FV) dimension reduction, is described. Feature-vector reduction (FVR) exploits the clustering of FV components for a given query. Clustering is based on the comparison of magnitudes of FV components of a query. Instead of all FV components describing color, line directions, and texture, only their representative members describing FV clusters are used for retrieval. In this way, the "curse of dimensionality" is bypassed since redundant components of a query FV are rejected. It was shown that about one tenth of total FV components (i.e., the reduction of 90%) is sufficient for retrieval, without significant degradation of accuracy. Consequently, the retrieving process is accelerated. Moreover, even better balancing between color and line/texture features is obtained. The efficiency of FVR CBIR system was tested over TRECVid 2006 and Corel 60 K datasets.

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Authors’ Affiliations

(1)
College of Information and Communication Technologies
(2)
Computer and Information Sciences Department, Information Science and Technology Center, Temple University
(3)
Digital Image Processing, Telemedicine and Multimedia Laboratory, Faculty of Electrical Engineering, University of Belgrade

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Copyright

© Goran Zajić et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.