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