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Research Paper #794

Title:Direct Least Squares Fitting of Ellipses
Authors:Fitzgibbon,AW; Pilu,M; Fisher,RB
Date:Jan 1996
Presented:Submitted to the International Conference on Pattern Recognition "96
Abstract:This work presents a new efficient method for fitting ellipses to scattared data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint $4ac -b^2 = 1$ the new method incorporates the ellipticity constraint into the normalization factor. The new method combines several advantages: (i) It is ellipse-specific so that even bad data will always return an ellipse; (ii) It can be solved naturally by a generalized eigensystem and (iii) it is extremely robust, efficient and easy to implement. We compare the proposed method to other approaches and show its robustness on several examples in which other non-ellipse-specific approaches would fail or require computationally expensive iterative refinements. Source code for the algorithm is supplied and a demonstration is available on

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