Texture-based Image Retrieval Based on FABEMD
In this paper, we present a new method for content based images
retrieval (CBIR). We propose characterizing images by using
global information extracted from the Fast and Adaptive
Bidimensional Empirical Mode Decomposition (FAEMD),
which decomposes image into a set of functions named
Bidimensional Intrinsic Mode Functions (BIMF) and a residue.
On the first two BIMFs, which contains a high frequency part of
the image, eventually curves and edges, Curvelet transform (CT)
was applied; wheras on the remaining part of the image Gabor
wavelets (GW) were applied. Image feature based on Curvelet
transform and Gabor wavelet, are then calculated. Our approach
was tested on Brodatz database. Experimental results show that
the proposed system outperforms previous rotation-invariant
systems significantly, and it is found to be superior to Curvelet
Transform and Gabor wavelets.
Keywords: Content Based Image Retrieval, FABEMD, Curvelet Transform, Gabor Wavelets
Download Full-Text