Skip to Main content Skip to Navigation
Conference papers

Recherche d'image par le contenu visuel utilisant la décomposition BEMD et le modéle Gamma généralisé des IMFS

Abstract : In this paper, we propose to characterize images without extracting local features, by using global information extracted from the image Bidimensinal Empirical Mode Decomposition (BEMD). This method decompose image into a set of functions named Intrinsic Mode Function (IMF) and residue. The Generalized Gamma Density function (GG) is used to represent the coefficients derived from each IMF, and the Kullback-Leibler Distance (KLD) compute the similarity between GGs. Results are promising: retrieval efficiency is higher than 86 % for same cases.
Complete list of metadata

https://hal.inria.fr/inria-00494809
Contributor : Conférence Sfds-Hal Connect in order to contact the contributor
Submitted on : Thursday, June 24, 2010 - 8:59:05 AM
Last modification on : Thursday, June 24, 2010 - 8:59:05 AM
Long-term archiving on: : Monday, September 27, 2010 - 11:41:35 AM

File

p221.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00494809, version 1

Collections

Citation

Aziza Benkuider, Abdelouahed Sabri, Abed Allah Aarab. Recherche d'image par le contenu visuel utilisant la décomposition BEMD et le modéle Gamma généralisé des IMFS. 42èmes Journées de Statistique, 2010, Marseille, France, France. ⟨inria-00494809⟩

Share

Metrics

Record views

96

Files downloads

101