Accelerating of Image Retrieval in CBIR System with Relevance Feedback

  • Goran ZajićEmail author
  • Nenad Kojić
  • Vladan Radosavljević
  • Maja Rudinac
  • Stevan Rudinac
  • Nikola Reljin
  • Irini Reljin
  • Branimir Reljin
Open Access
Research Article
Part of the following topical collections:
  1. Knowledge-Assisted Media Analysis for Interactive Multimedia Applications


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.


Color Information Technology Quantum Information Image Retrieval Dimension Reduction 


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Copyright information

© 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.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Goran Zajić
    • 1
    Email author
  • Nenad Kojić
    • 1
  • Vladan Radosavljević
    • 2
  • Maja Rudinac
    • 1
  • Stevan Rudinac
    • 3
  • Nikola Reljin
    • 1
  • Irini Reljin
    • 1
    • 3
  • Branimir Reljin
    • 3
  1. 1.College of Information and Communication TechnologiesBelgradeSerbia
  2. 2.Computer and Information Sciences Department, Information Science and Technology CenterTemple UniversityPhiladelphiaUSA
  3. 3.Digital Image Processing, Telemedicine and Multimedia Laboratory, Faculty of Electrical EngineeringUniversity of BelgradeBelgradeSerbia

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