DocumentCode :
2832738
Title :
Quadtree classified vector quantization based image retrieval scheme
Author :
Chen, Hsin-Hui ; Sheu, Hsin-Teng ; Ding, Jian-Jiun
Author_Institution :
Grad. Inst. of Commun. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
3625
Lastpage :
3628
Abstract :
With the fast development of multimedia, it is crucial to find the way to search image database effectively. The vector quantization (VQ) based image retrieval method is popular in recent years. In this paper, we propose the quadtree classified vector quantization (QCVQ) scheme to improve the VQ method by exploiting the visual importance of image blocks and using the edge information to describe the content of each block efficiently. Moreover, we also apply the adaptive block size. The simulation results show that, compared with the previous image retrieval algorithms using VQ and chromaticity moments (CM), our proposed scheme has obviously better average retrieval rate and higher average precision.
Keywords :
image coding; image retrieval; trees (mathematics); vector quantisation; adaptive block size; chromaticity moments; image database searching; image retrieval scheme; multimedia; quadtree classified vector quantization; Histograms; Image coding; Image edge detection; Image retrieval; Image segmentation; Vector quantization; content based retrieval; image databases; image retrieval; multimedia databases; vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
ISSN :
1522-4880
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2011.6116503
Filename :
6116503
Link To Document :
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