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Region Based Color Image Retrieval Using Curvelet Transform

  • Md. Monirul Islam
  • Dengsheng Zhang
  • Guojun Lu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5995)

Abstract

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.

Keywords

Image Retrieval Gabor Filter Retrieval Performance Gabor Feature Query Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Md. Monirul Islam
    • 1
  • Dengsheng Zhang
    • 1
  • Guojun Lu
    • 1
  1. 1.Gippsland School of Information TechnologyMonash UniversityAustralia

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