• DocumentCode
    493578
  • Title

    Image Matching Based on Local Invariant Feature and Histogram-Based Similar Distance

  • Author

    Shan, Baoming ; Cui, Fengying

  • Author_Institution
    Coll. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao
  • Volume
    1
  • fYear
    2009
  • fDate
    7-8 March 2009
  • Firstpage
    1030
  • Lastpage
    1033
  • Abstract
    In this paper we present a novel approach combining local invariant feature descriptor ARPIH (Angular Radial Partitioning Intensity Histogram) with histogram-based similar distance (HSD). The method succeeds the descriptorpsilas distinctiveness and provides higher robustness for image deformations, such as rotation, illumination changing and perspective, etc. We present the HSD to calculate the number of the similar points between template image and target image in order to decrease the calculation complicacy and improve the matching precision. The matching results show good performance of our approach for both geometric deformations and illumination changing.
  • Keywords
    deformation; image matching; angular radial partitioning intensity histogram; histogram-based similar distance; image deformation; image matching; local invariant feature; target image; template image; Biomedical imaging; Computer science; Computer science education; Educational institutions; Educational technology; Gray-scale; Histograms; Image matching; Lighting; Robustness; ARPIH; HSD; image matching; local invariant feature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-1-4244-3581-4
  • Type

    conf

  • DOI
    10.1109/ETCS.2009.235
  • Filename
    4958939