Improving Shape-Based CBIR for Natural Image Content Using a Modified GFD

  • Yupeng Li
  • Matthew J. Kyan
  • Ling Guan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3656)


We present a modified version of the Generic Fourier Descriptor (GFD) that operates on edge information within natural images from the COREL image database for the purpose of shape-based image retrieval. By incorporating an edge-texture characterization (ETC) measure, we reduce the complexity inherent in oversensitive edge maps typical of most gradient-based detectors that otherwise tend to contaminate the shape feature description. We find that the proposed techniques not only improve overall retrieval in terms of shape, but more importantly, provide for a more accurate similarity ranking of retrieved results, demonstrating greater consideration for dominant internal and external shape details.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yupeng Li
    • 1
  • Matthew J. Kyan
    • 2
  • Ling Guan
    • 1
  1. 1.Multimedia Research LaboratoryRyerson UniversityTorontoCanada
  2. 2.School of Electrical & Information EngineeringUniversity of SydneyAustralia

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