Adaptive region matching for region-based image retrieval by constructing region importance index

被引:19
作者
Yang, Xiaohui [1 ]
Cai, Lijun [1 ]
机构
[1] Henan Univ, Inst Appl Math, Sch Math & Informat Sci, Dept Informat & Comp Sci, Kaifeng 475004, Peoples R China
基金
中国国家自然科学基金;
关键词
RECOGNITION; FEATURES;
D O I
10.1049/iet-cvi.2012.0157
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study deals with the problem of similarity matching in region-based image retrieval (RBIR). A novel visual similarity measurement called adaptive region matching (ARM) has been developed. For decreasing negative influence of interference regions and important information loss simultaneously, a region importance index is constructed and semantic meaningful region (SMR) is introduced. Moreover, ARM automatically performs SMR-to-image matching or image-to-image matching. Extensive experiments on Corel-1000, Caltech-256 and University of Washington (UW) databases demonstrate the authors proposed ARM is more flexible and more efficient than the existing visual similarity measurements that were originally developed for RBIR.
引用
收藏
页码:141 / 151
页数:11
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