Ahn, S.J.S.J.AhnRauh, W.W.RauhRecknagel, M.M.Recknagel2022-03-092022-03-091999https://publica.fraunhofer.de/handle/publica/333357The least squares fitting minimizes the squares sum of error-of-fit in predefined measures. By the geometric fitting, the error distances are defined with the shortest distances from the given points to the geometric feature to be fitted. For the geometric fitting of ellipse, a robust algorithm is proposed. This is based on the coordinate description of the corresponding point on the ellipse for the given point, where the connecting line of the two points is the shortest path from the given point to the ellipse. As a practical application example, we show the geometric ellipse fitting to the image of circular point targets, where the contour points are weighted with their image gradient across the boundary of the image ellipse.enEllipse FittingNonlinear Least SquaresCircular Object targetOrthogonal Error Distanceedge detection670conference paper