DocumentCode :
3543385
Title :
Rotation invariant fuzzy shape contexts based on Eigenshapes and fourier transforms for efficient radiological image retrieval
Author :
Ben Ayed, Alaidine ; Kardouchi, Mustapha ; Selouani, Sid-Ahmed
Author_Institution :
Dept. d´´Inf., Univ. de Moncton, Moncton, NB, Canada
fYear :
2012
fDate :
10-12 May 2012
Firstpage :
266
Lastpage :
271
Abstract :
This paper proposes a new descriptor for radiological image retrieval. The proposed approach is based on fuzzy shape contexts, Fourier transforms and Eigenshapes. At first, fuzzy shape context histograms are computed. Then, a 2D FFT is performed on each 2D histogram to achieve rotation invariance. Next, histograms are projected onto a lower dimensionality feature space. The new space is more representative. It highlights the most important variations between shapes. Eigenshapes are the principal components for radiological images. 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 robust to local deformations and more efficient.
Keywords :
eigenvalues and eigenfunctions; fast Fourier transforms; fuzzy set theory; image retrieval; medical image processing; radiology; 2D FFT; 2D histogram; Fourier transforms; eigenshape; fuzzy shape context histogram; medical IRMA database; radiological image retrieval; rotation invariant fuzzy shape context; Biomedical imaging; Cancer; Context; Image recognition; Robustness; Shape; Eigenshapes; Fourier transform; Fuzzy Shape contexts; Image retrieval; Radiological images;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2012 International Conference on
Conference_Location :
Tangier
Print_ISBN :
978-1-4673-1518-0
Type :
conf
DOI :
10.1109/ICMCS.2012.6320294
Filename :
6320294
Link To Document :
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