• DocumentCode
    2078437
  • Title

    Geometric heat equation and nonlinear diffusion of shapes and images

  • Author

    Kimia, Benjamin B. ; Siddiqi, Kaleem

  • Author_Institution
    Div. of Eng., Brown Univ., Providence, RI, USA
  • fYear
    1994
  • fDate
    21-23 Jun 1994
  • Firstpage
    113
  • Lastpage
    120
  • Abstract
    We propose a geometric smoothing method based on local curvature in shapes and images which is governed by the geometric heat equation and is a special case of the reaction-diffusion framework proposed by Faugeras (1990). For shapes, the approach is analogous to the classical heat equation smoothing, but with a renormalization by arc-length at each infinitesimal step. For images, the smoothing is similar to anisotropic diffusion in that, since the component of diffusion in the direction of the brightness gradient is nil, edge location and sharpness are left intact. We present several properties of curvature deformation smoothing of shape: it preserves inclusion order, annihilates extrema and inflection points without creating new ones, decreases total curvature, satisfies the semi-group property allowing for local iterative computations, etc. Curvature deformation smoothing of an image is based on viewing it as a collection of iso-intensity level sets, each of which is smoothed by curvature and then reassembled. This is shown to be mathematically sound and applicable to medical, aerial and range images
  • Keywords
    computational geometry; edge detection; anisotropic diffusion; arc-length; brightness gradient; classical heat equation smoothing; curvature deformation smoothing; edge location; geometric heat equation; geometric smoothing method; inclusion order; inflection points; local curvature; local iterative computation; nonlinear diffusion; reaction-diffusion framework; shape curvature; sharpness; Geometric modeling; Image line-pattern analysis; Image shape analysis; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on
  • Conference_Location
    Seattle, WA
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-5825-8
  • Type

    conf

  • DOI
    10.1109/CVPR.1994.323817
  • Filename
    323817