STUDY ON A ROUGH SET APPROACH TO SEMANTIC IMAGE RETRIEVAL

摘要：

In this paper, semantic gap is a challenging issue in image retrieval. Firstly, in the process of constructing vector space model, the theory of Latent Semantic Indexing is introduced to mine the semantic information of images, and then, rough set theory is applied to retrieve and match the semantic feature of image database in the approximate space of tolerance rough set. Lastly, semantic image classification algorithm is implemented. Experimental results show that the performance of the classification is greatly improved.

关键词： semantic gap image retrieval tolerance rough set

作者: Qingmin Cui Wangao Li

作者单位: School of Computer Science and Engineering, Henan Institute of Engineering, Zhenzhou,451191ChinaNetw School of Computer Science and Engineering, Henan Institute of Engineering, Zhenzhou,451191China Net

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

会议地点: 北京

会议语种:英文

页码: 879-882

在线出版日期: 2010-10-26（万方平台首次上网日期，不代表论文的发表时间）