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
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