DocumentCode :
59347
Title :
Adaptive region matching for region-based image retrieval by constructing region importance index
Author :
XiaoHui Yang ; Lijun Cai
Author_Institution :
Dept. of Inf. & Comput. Sci., Henan Univ., Kaifeng, China
Volume :
8
Issue :
2
fYear :
2014
fDate :
Apr-14
Firstpage :
141
Lastpage :
151
Abstract :
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.
Keywords :
image matching; image retrieval; interference; visual databases; ARM; Caltech-256 database; Corel-1000 database; RBIR; SMR-to-image matching; UW database; adaptive region matching; image-to-image matching; interference regions; region importance index; region-based image retrieval; semantic meaningful region; similarity matching problem; visual similarity measurement;
fLanguage :
English
Journal_Title :
Computer Vision, IET
Publisher :
iet
ISSN :
1751-9632
Type :
jour
DOI :
10.1049/iet-cvi.2012.0157
Filename :
6781764
Link To Document :
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