• DocumentCode
    2542366
  • Title

    3D Gray Level Moment Invariants: A Novel Shape Representation

  • Author

    Guo, Kehua ; Li, Min

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
  • fYear
    2009
  • fDate
    4-6 Nov. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    3D moment invariants are traditionally based on region characteristics and the location of every pixel point, this will cause high calculation cost. In this paper, a novel shape representation named 3D gray level moment invariants is constructed. Some properties of the new representation including the independence of the translation, scaling and rotation transforms are proved. Experiments indicate an encouraging high recognition rates without reducing the recognition performance compared with traditional methods.
  • Keywords
    image representation; transforms; 3D moment invariant; 3Dshape representation; Application software; Computer vision; Costs; Image reconstruction; Image segmentation; Information science; Noise shaping; Object recognition; Shape; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4199-0
  • Type

    conf

  • DOI
    10.1109/CCPR.2009.5344066
  • Filename
    5344066