• DocumentCode
    2621106
  • Title

    Ellipse-specific direct least-square fitting

  • Author

    Pilu, Maurixio ; Fitzgibbon, Andrew W. ; Fisher, Robert B.

  • Author_Institution
    Dept. of Artificial Intelligence, Edinburgh Univ., UK
  • Volume
    3
  • fYear
    1996
  • fDate
    16-19 Sep 1996
  • Firstpage
    599
  • Abstract
    Ellipse fitting is one of the classic problems of pattern recognition and has been subject to considerable attention because of its many applications. This article presents the first direct method for specifically fitting ellipses in the least squares sense. Previous approaches used either generic conic fitting or relied on iterative methods to recover elliptic solutions. The proposed method is (i) ellipse-specific, (ii) directly solved by a generalised eigen-system, (iii) has a desirable low-eccentricity bias, and (iv) is robust to noise. We provide a theoretical demonstration, several examples and the Matlab coding of the algorithm
  • Keywords
    curve fitting; eigenvalues and eigenfunctions; least squares approximations; pattern recognition; Matlab coding; algorithm; direct least-square fitting; direct method; ellipse fitting; elliptic solutions; generalised eigensystem; generic conic fitting; iterative methods; low-eccentricity bias; noise robustness; pattern recognition; Artificial intelligence; Iterative algorithms; Iterative methods; Least squares approximation; Least squares methods; Minimization methods; Noise robustness; Pattern recognition; Polynomials; Scattering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1996. Proceedings., International Conference on
  • Conference_Location
    Lausanne
  • Print_ISBN
    0-7803-3259-8
  • Type

    conf

  • DOI
    10.1109/ICIP.1996.560566
  • Filename
    560566