Title :
Content based image retrieval using curvelet transform
Author :
Sumana, Ishrat Jahan ; Islam, Md Monirul ; Zhang, Dengsheng ; Lu, Guojun
Author_Institution :
Gippsland Sch. of Inf. Technol., Monash Univ., Churchill, VIC
Abstract :
Feature extraction is a key issue in content-based image retrieval (CBIR). In the past, a number of texture features have been proposed in literature, including statistic methods and spectral methods. However, most of them are not able to accurately capture the edge information which is the most important texture feature in an image. Recent researches on multi-scale analysis, especially the curvelet research, provide good opportunity to extract more accurate texture feature for image retrieval. Curvelet was originally proposed for image denoising and has shown promising performance. In this paper, a new image feature based on curvelet transform has been proposed. We apply discrete curvelet transform on texture images and compute the low order statistics from the transformed images. Images are then represented using the extracted texture features. Retrieval results show, it significantly outperforms the widely used Gabor texture feature.
Keywords :
content-based retrieval; discrete wavelet transforms; feature extraction; image denoising; image texture; statistical analysis; Gabor texture feature; content based image retrieval; discrete curvelet transform; feature extraction; image denoising; multiscale analysis; spectral methods; statistic methods; Content based retrieval; Data mining; Discrete transforms; Image analysis; Image databases; Image denoising; Image retrieval; Image texture analysis; Information retrieval; Statistics;
Conference_Titel :
Multimedia Signal Processing, 2008 IEEE 10th Workshop on
Conference_Location :
Cairns, Qld
Print_ISBN :
978-1-4244-2294-4
Electronic_ISBN :
978-1-4244-2295-1
DOI :
10.1109/MMSP.2008.4665041