An efficient image retrieval model using fuzzy semantic concepts

被引:0
|
作者
Chang, Tsun-Wei [1 ]
Huang, Yo-Ping [1 ]
Sandnes, Frode Eika [2 ]
机构
[1] Tatung Univ, Dept Comp Sci & Engn, Taipei 10451, Taiwan
[2] Oslo Univ Coll, Fac Engn, Oslo, Norway
来源
NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY | 2007年
关键词
fuzzy semantic concepts; fuzzy SOM; fuzzy centrality; fuzzy intensity;
D O I
10.1109/NAFIPS.2007.383842
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Concepts can add knowledge to the interpretation of image contents. However, mapping low-level features to high-level image semantics is still an ongoing challenge for researchers. In this paper an integrated model of fuzzy centrality and intensity concepts, together with the concept hierarchy is proposed to efficiently retrieving images. The self-organization feature map is applied to construct a three-layer concept hierarchy for image archives. Thus, search for the image concepts can be effectively achieved by detecting the presences of the relevant bottom-level image primitive features. In other words, an image can be categorized into multiple semantics. Consequently, the retrieval accuracy can be improved by searching the multiple categories. The methodology of the proposed model will be illustrated in this paper and the experimental results will be presented to demonstrate the efficiency in retrieving images.
引用
收藏
页码:227 / +
页数:2
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