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Proceedings Paper

A method for semantic-based image retrieval
Author(s): Hengwen Liu; Hengqing Tong; Qiaoling Tong
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Paper Abstract

The most existed content-based image retrieval systems use traditional low-level features such as color, texture and shape to describe the image content, which are usually represented by statistic data. Actually, there are big differences between these statistic data and the image content which people understand. Therefore, how to describe image and to make it coincide with people's understanding become the key point of improving retrieval accuracy. In the point of cognition, people's understanding and description of image content is on semantic level. How to reduce 'semantic gap', how to accurately represent content semantic of image and retrieval intention of people becomes important and critical. One effective ways has been proposed to solve the problem: semantic image retrieval based on ontology. In this paper a new image retrieval system based on ontology and relevant feedback was presented. The ontology was used to describe the semantic features of images and then retrieve the images.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74954J (30 October 2009); doi: 10.1117/12.833928
Show Author Affiliations
Hengwen Liu, Wuhan Univ. of Technology (China)
Hengqing Tong, Wuhan Univ. of Technology (China)
Qiaoling Tong, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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