• DocumentCode
    2226632
  • Title

    A Novel Shape Descriptor: Gaussian Curvature Moment Invariants

  • Author

    Guo Kehua ; Li Min

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Central South Univ., Changsha, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    1087
  • Lastpage
    1090
  • Abstract
    The moment descriptor is combined with Gaussian curvature for three-dimensional shape representation and a novel three-dimensional shape descriptor combined local with global representations is proposed in this paper. Normalization process to the new moment invariants is presented and their independence to the translation, rotation and scaling transforms is proved. Experiments indicate a better classification result to objects with slight different shape characteristic compared with some traditional approaches without increasing the running complexity.
  • Keywords
    Gaussian processes; computational geometry; image classification; object recognition; shape recognition; Gaussian curvature moment invariants; classification result; global representations; moment descriptor; moment invariants; normalization process; rotation; running complexity; scaling transforms; shape descriptor; three-dimensional shape representation; translation transforms; Character recognition; Image segmentation; Information science; Kernel; MPEG 7 Standard; Moment methods; Noise shaping; Pattern recognition; Robustness; Shape measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.125
  • Filename
    5455286