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ASME Press Select Proceedings
International Conference on Advanced Computer Theory and Engineering, 5th (ICACTE 2012)
Editor
ISBN:
9780791860045
No. of Pages:
938
Publisher:
ASME Press
Publication date:
2012
eBook Chapter
28 Contourlet Texture Retrieval Algorithm with Two Energy and Kurtosis Features
By
Page Count:
6
-
Published:2012
Citation
Li-Wei, L, & Xin-Wu, C. "Contourlet Texture Retrieval Algorithm with Two Energy and Kurtosis Features." International Conference on Advanced Computer Theory and Engineering, 5th (ICACTE 2012). Ed. Yi, X. ASME Press, 2012.
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Contourlet texture image retrieval algorithm can achieve higher retrieval rates than wavelet ones under same structure due to much finer directional information representation than wavelet transform and have been studied by many researchers. In order to improve the retrieval rate further, a new contourlet transform based texture image retrieval system was proposed in this paper. In the system, absolute mean sub-bands energy, L2-energy and kurtosis in contourlet domain were cascaded to form feature vectors, and the similarity metric was Canberra distance. Experimental results show that this contourlet transform based image retrieval system is superior to that of the contourlet transform...
1. Introduction
2. Key Techniques of this New Contourlet Texture Image Retrieval Algorithm
3. Experiment and Results
4. Conclusions
Acknowledgements
References
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