• DocumentCode
    1839657
  • Title

    Arc-length based curvature estimator

  • Author

    Lewiner, Thomas ; Gomes, João D., Jr. ; Lopes, Hélio ; Craizer, Marcos

  • Author_Institution
    Departamento de Matematica, Pontificia Univ. Catolica do Rio de Janeiro, Brazil
  • fYear
    2004
  • fDate
    17-20 Oct. 2004
  • Firstpage
    250
  • Lastpage
    257
  • Abstract
    Many applications of geometry processing and computer vision rely on geometric properties of curves, particularly their curvature. Several methods have been proposed to estimate the curvature of a planar curve, most of them for curves in digital spaces. This work proposes a new method for curvature estimation based on weighted least square fitting and local arc-length approximation. Convergence analysis of this method and noise impact on the estimator accuracy are given. Numerical robustness issues are addressed with practical solutions. The implementation of the method is compared to other curvature estimation methods.
  • Keywords
    computational geometry; computer vision; convergence of numerical methods; curvature measurement; differential geometry; least squares approximations; computer vision; convergence analysis; curvature estimator; curves; geometry processing; local arc-length approximation; noise impact; weighted least square fitting; Application software; Computational geometry; Computer graphics; Computer vision; Curve fitting; Image reconstruction; Least squares approximation; Noise robustness; Particle measurements; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Graphics and Image Processing, 2004. Proceedings. 17th Brazilian Symposium on
  • ISSN
    1530-1834
  • Print_ISBN
    0-7695-2227-0
  • Type

    conf

  • DOI
    10.1109/SIBGRA.2004.1352968
  • Filename
    1352968