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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Liu, Y., et al.: Region-based image retrieval with high-level semantics using decision tree learning. Patt. Recog. 41(8), 2554–2570 (2008)
Manjunath, B.S., Ma, W.Y.: Texture Features for Browsing and Retrieval of Large Image Data. IEEE Trans. on PAMI 18(8), 837–842 (1996)
Manjunath, B.S., et al.: Introduction to MPEG-7. John Wiley & Son Ltd., Chichester (2002)
Bhagavathy, S., Chhabra, K.: A Wavelet-based Image Retrieval System. Technical Report—ECE278A, Vision Research Laboratory, University of California, Santa Barbara (2007)
Do, M.N.: Directional Multiresolution Image Representations. PhD Thesis, EPFL (2001)
Starck, J., et al.: The Curvelet Transform for Image Denoising. IEEE Trans. on Image Processing 11(6), 670–684 (2002)
Majumdar, A.: Bangla Basic Character Recognition Using Digital Curvelet Transform. Journal of Pattern Recognition Research 1, 17–26 (2007)
Sumana, I.J., et al.: Content based image retrieval using curvelet transform. In: Proc. of Int. workshop on MMSP, pp. 11–16 (2008)
Wang, J.Z., et al.: Simplicity: semantics-sensitive integrated matching for picture libraries. IEEE Trans. on PAMI 23(9), 947–963 (2001)
Liu, Y.: Region-based image retrieval with high-level semantics. Ph. D. Thesis, Monash University (2006)
Candes, E., et al.: Fast Discrete Curvelet Transforms. Multiscale Modeling and Simulation 5(3), 861–899 (2006)
Coreman, T.H., et al.: Introduction to Algorithms. The MIT Press, Cambridge (2001)
Deng, Y., Manjunath, B.S.: Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. on PAMI 23(8), 800–810 (2001)
Manjunath, B.S., Ma, W.Y.: Texture features for browsing and retrieval of image data. IEEE Trans. on PAMI 18(8), 837–842 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Islam, M.M., Zhang, D., Lu, G. (2010). Region Based Color Image Retrieval Using Curvelet Transform. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-12304-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12303-0
Online ISBN: 978-3-642-12304-7
eBook Packages: Computer ScienceComputer Science (R0)