IMAGE RETRIEVAL WITH FEATURE SELECTION AND RELEVANCE FEEDBACK

被引：14
|
作者：
Sun, Yu [1 ]
Bhanu, Bir [1 ]
机构：
[1] Univ Calif Riverside, Ctr Res Intelligent Syst, Riverside, CA 92521 USA
来源：
2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年
关键词：
CBIR; Relevance Feedback; Feature Selection;
D O I：
10.1109/ICIP.2010.5651984
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from relevance feedback is explicitly used as a new semantic criterion to guide the feature selection. By integrating the user feedback information, the feature selection is able to bridge the gap between low-level visual features and high-level semantic information, leading to the improved image retrieval accuracy. Experimental results show that the proposed method obtains higher retrieval accuracy than a commonly used approach.
引用
收藏
页码：3209 / 3212
页数：4
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