Efficient Image Retrieval Using Support Vector Machines and Bayesian Relevance Feedback

被引：0
|
作者：
Wang, XueFeng [1 ]
Chen, XingSu [1 ]
机构：
[1] YiLi Normal Univ, Sch Elect & Informat Engn, Yining Xingjiang, Peoples R China
来源：
2012 5TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP) | 2012年
关键词：
content-based image retrieval(CBIR); support vector machines(SVM); Bayesian; relevance feedback;
D O I：
暂无
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：
Content-based image retrieval is an active research area in image processing. Recently, many researchers have employed support vector machines (SVMs) for image retrieval research area. This paper presents a multiple support vector machines for image classification in the first stage; and then according to the user's marked images, we use relevance feedback based on Bayesian methodology, which yields the posteriori of the images in the database; The retrieval system can repeated by user during the relevance feedback stage. Experimental results based on a set of Corel images demonstrate that the proposed system achieves high performance.
引用
收藏
页码：786 / 789
页数：4
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