Ellipse Fit (Taubin method)

This is a fast non-iterative ellipse fit, and among fast non-iterative ellipse fits this is the most accurate and robust.

It takes the xy-coordinates of data points, and returns the coefficients of the equation of the ellipse:

ax^2 + bxy + cy^2 + dx + ey + f = 0,

i.e. it returns the vector A=(a,b,c,d,e,f). To convert this vector to the geometric parameters (semi-axes, center, etc.), use standard formulas, see e.g., (19) - (24) in Wolfram Mathworld: http://mathworld.wolfram.com/Ellipse.html

This fit was proposed by G. Taubin in article "Estimation Of Planar Curves, Surfaces And Nonplanar Space Curves Defined By Implicit Equations, With Applications To Edge And Range Image Segmentation", IEEE Trans. PAMI, Vol. 13, pages 1115-1138, (1991).

Note: this method fits a quadratic curve (conic) to a set of points; if points are better approximated by a hyperbola, this fit will return a hyperbola. To fit ellipses only, use "Direct Ellipse Fit".