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
Link To Document