DocumentCode :
2736333
Title :
A method of measuring the semantic gap in image retrieval: Using the information theory
Author :
Liu, Chengjun ; Song, Guangwei
Author_Institution :
Manage. Dept., Shenzhen Univ., Shenzhen, China
fYear :
2011
fDate :
21-23 Oct. 2011
Firstpage :
287
Lastpage :
291
Abstract :
The semantic gap exists in content-based image retrieval. Many researchers have proposed a variety of methods to bridge or narrow this gap. The methods include into two types: bottom-up and top-down approaches. These approaches have made great progress, but few studies have been done in how to measure it. In this paper, we redefine the semantic gap in a user-centered way and present a method for measuring the semantic gap, using the information theory.
Keywords :
content-based retrieval; image retrieval; information theory; bottom-up approach; content-based image retrieval; information theory; semantic gap measurement method; top-down approach; Computers; Feature extraction; Image color analysis; Image retrieval; Ontologies; Semantics; Sun; content-based image retrieval; definition; information entropy; measuring; semantic gap;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2011 International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-1-61284-879-2
Type :
conf
DOI :
10.1109/IASP.2011.6109048
Filename :
6109048
Link To Document :
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