• 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