Rotation Invariant Fuzzy Shape Contexts Based on Eigenshapes and Fourier Transforms for Efficient Radiological Image Retrieval

  • Alaidine Ben Ayed
  • Mustapha Kardouchi
  • Sid-Ahmed Selouani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)


This paper proposes a new descriptor for radiological image retrieval. The proposed approach is based on fuzzy shape contexts, Fourier transforms and Eigenshapes. First, fuzzy shape context histograms are computed. Then, a 2D FFT is performed on each 2D histogram to achieve rotation invariance. Finally, histograms are projected onto a lower dimensionality feature space whose basis is formed by a set of vectors called Eigenshapes. They highlight the most important variations between shapes. The proposed approach is translation, scale and rotation invariant. Classes of the medical IRMA database are used for experiments. Comparison with the known approach rotation invariant shape contexts based on feature-space Fourier transformation proves that the proposed method is faster, more efficient, and robust to local deformations.


Image retrieval Fuzzy Shape Contexts Fourier transform Eigenshapes Radiological images 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alaidine Ben Ayed
    • 1
  • Mustapha Kardouchi
    • 1
  • Sid-Ahmed Selouani
    • 2
  1. 1.Université de MonctonMonctonCanada
  2. 2.Université de MonctonShippaganCanada

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