Direct least square fitting of ellipses

This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac-b/sup 2/=1, the new method incorporates the ellipticity constraint...

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Bibliographic Details
Published inIEEE transactions on pattern analysis and machine intelligence Vol. 21; no. 5; pp. 476 - 480
Main Authors Fitzgibbon, A., Pilu, M., Fisher, R.B.
Format Journal Article
LanguageEnglish
Published IEEE 01.05.1999
Subjects
Algebra
Algorithms
Application software
Computer vision
Conics
Eigenvalues and eigenfunctions
Ellipses
Fitting
Fittings
Intelligence
Iterative algorithms
Iterative methods
Least squares method
Least squares methods
Pattern analysis
Pattern recognition
Robustness
Scattering
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ISSN0162-8828
DOI10.1109/34.765658

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Summary:This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac-b/sup 2/=1, the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: It is ellipse-specific, so that even bad data will always return an ellipse. It can be solved naturally by a generalized eigensystem. It is extremely robust, efficient, and easy to implement.
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ISSN:0162-8828
DOI:10.1109/34.765658