This paper presents a robust and accurate technique for an estimation of
the best-fit ellipse going through the given set of points. The approach is
based on a least squares minimization of algebraic distances of the
points with a correction of the statistical bias caused during the
computation. An accurate ellipse-specific solution is guaranteed even
for scattered or noisy data with outliers. Although the final algorithm
is iterative, it typically converges in a fraction of time needed for a
true orthogonal fitting based on Eucleidan distances of points.