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.
Origin : Files produced by the author(s)