Direct least square fitting of ellipses

Andrew Fitzgibbon(University of Edinburgh), M. Pilu(Hewlett-Packard (United States)), Robert B. Fisher(University of Edinburgh)
IEEE Transactions on Pattern Analysis and Machine Intelligence
May 1, 1999
Cited by 2,721

Abstract

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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