This is a robust and accurate circle fit. It works well even if data
points are observed only within a small arc. This circle 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). It is more stable than the simple Circle Fit by Kasa (files
#5557 and #22642) and slightly faster than Circle Fit by Pratt (file #22643).
Nikolai Chernov (2019). Circle Fit (Taubin method) (https://www.mathworks.com/matlabcentral/fileexchange/22678-circle-fit-taubin-method), MATLAB Central File Exchange. Retrieved .
Can anyone help me with using this function in the Curve Fitting App ? I need to get Goodness of Fit and RSME values..
Nice ! Would be nice to input sigma error on data points and output resulting error on center and radius.
Works nicely, can be easily extended to 3D data.
%project 3D data to a plane
XYp = U'*XYr;
Pare = CircleFitByTaubin(XYp(1:2,:)')
UU = U * [Pare(1:2)';0];
RR = Pare(end);
Nice function. Very clean and easily implemented in any language. Was wondering if it could be extended to a sphere. I can't follow how you wrote the function from the article (G. Taubin, 1991)
Inspired by: Circle fit