Content Based Image Retrieval using the Generalized Gamma Density to model BEMD’s IMF.
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| Title | Content Based Image Retrieval using the Generalized Gamma Density to model BEMD’s IMF. |
| Authors | |
| Abstract | In this paper, we present a texture-image retrieval approach, which is based on the idea of to characterize images without extracting local features, by using global information extracted from the image Bidimensinal Empirical Mode Decomposition (BEMD) together with the Generalized Gamma (GG) Density. The BEMD method decompose image into a set of functions named Intrinsic Mode Function (IMF) and residue. The Generalized Gamma (GG) Density is used to represent the coefficients derived from each IMF and the Kullback-Leibler Distance (KLD) compute the similarity between Gamma Generalized function’s coefficients. The experimental results indicate that our approach can achieve higher retrieval rates. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2011-06-03 |
| Source | Journal of Computers Vol 6, No 6 (2011): Special Issue: Advances in Modeling and Simulation |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |