Semantic-based image retrieval: A fuzzy modeling approach

被引：6
|
作者：
Lakdashti, Abolfazl [1 ]
Moin, M. Shahram [2 ]
Badie, Kambiz [2 ]
机构：
[1] Islamic Azad Univ, Sci & Res Branch, Rouzbahan Inst Higher Educ, Sari, Iran
[2] Iran Telecommun Res Ctr, IT Fac, Tehran, Iran
来源：
2008 IEEE/ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, VOLS 1-3 | 2008年
关键词：
D O I：
10.1109/AICCSA.2008.4493589
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a new fuzzy based image retrieval approach to reduce the semantic gap in content-based image retrieval systems. Our main contributions are: (1) an algorithm for reduction of feature space dimensionality, (2) a fuzzy modeling approach to model the expert human behavior in the image retrieval task, (3) a fuzzy system for semantic-based image retrieval, and (4) a training algorithm for creating the fuzzy rules. The proposed solution not only is a novel idea in the semantic-based image retrieval field, but also has enough potential in learning semantics from users and making a powerful approach to improve the performance of CBIR systems, as the results of our experiments on a set of 2000 images support our claim.
引用
收藏
页码：575 / +
页数：3
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