Adaptive region matching for region‐based image retrieval by constructing region importance index
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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2012.0157 |
| Summary: | 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. |
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| ISSN: | 1751-9632 1751-9640 |