Region Based Color Image Retrieval Using Curvelet Transform

Region based image retrieval has received significant attention from recent researches because it can provide local description of images, object based query, and semantic learning. In this paper, we apply curvelet transform to region based retrieval of color images. The curvelet transform has shown promising result in image de-noising, character recognition, and texture image retrieval. However, curvelet feature extraction for segmented regions is challenging because it requires regular (e.g., rectangular) shape images or regions, while segmented regions are usually irregular. An efficient method is proposed to convert irregular regions to regular regions. Discrete curvelet transform can then be applied on these regular shape regions. Experimental results and analyses show the effectiveness of the proposed shape transform method. We also show the curvelet feature extracted from the transformed regions outperforms the widely used Gabor features in retrieving natural color images.