DocumentCode :
442515
Title :
Color texture retrieval through contourlet-based hidden Markov model
Author :
He, Zhihua ; Bystrom, Maja
Author_Institution :
Dept. of ECE, Boston Univ., MA, USA
Volume :
1
fYear :
2005
fDate :
11-14 Sept. 2005
Abstract :
Two statistical models for color texture retrieval based on a hidden Markov model (HMM) in the contourlet domain are described in this paper. Through a contourlet transformation, each color component of an image is decomposed into a set of directional subbands with texture details captured in different orientations. By exploiting inter-scale dependencies and in-band spatial dependencies, the distribution of the coefficients in each subband triplet (subbands of three color components at the same scale with the same orientation) can be estimated using a vector hidden Markov model. The Kullback-Leibler distance (KLD) is used to measure the difference between the distributions of query texture images and those of images in the database. The experimental results show the proposed retrieval systems yield high retrieval rates and better visual quality as compared with previous methods employing hidden Markov models for luminance component alone.
Keywords :
hidden Markov models; image colour analysis; image retrieval; image texture; Kullback-Leibler distance; color texture retrieval; contourlet-based hidden Markov model; Feature extraction; Helium; Hidden Markov models; Image databases; Image retrieval; Information retrieval; Sections; Visual databases; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
Type :
conf
DOI :
10.1109/ICIP.2005.1529800
Filename :
1529800
Link To Document :
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