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J4  2009, Vol. 43 Issue (12): 2129-2135    DOI: 10.3785/j.issn.1008-973X.2009.12.001
Improved Web image retrieval by weighted image annotations
HUANG Peng, CHEN Chun, WANG Can, BU Jia-jun, CHEN  Wei, QIU Guang
(Zhejiang Key Laboratory of Service Robot, Zhejiang University, Hangzhou 310027, China)
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A Web image retrieval method was proposed which combines textual terms extracted from Web documents and image contents in order to improve Web image retrieval.  Web  image contents were translated into image annotations by the improved automatic image annotation model. Then the technology of term similarity measurement, as the metric form of  semantic information, was applied to weighting image annotations. These annotations and some terms extracted from Web documents were introduced into Web image retrieval under  the framework of Bayesian  inference network which has an inherent fusion capability of multiple information sources. Experimental results show that the  method improves image  retrieval to some extent by combining Web image contents and terms in Web documents.

Published: 16 January 2010
CLC:  TP 391.41  
Cite this article:

HUANG Feng, CHEN Chun, WANG Can, et al. Improved Web image retrieval by weighted image annotations. J4, 2009, 43(12): 2129-2135.

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