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 :
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