Least-squares orthogonal distances fitting of circle, sphere, ellipse, hyperbola, and parabola

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摘要

The 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 orthogonal, or shortest, distances from the given points to the geometric feature to be fitted. For the geometric fitting of circle/sphere/ellipse/hyperbola/parabola, simple and robust nonparametric algorithms are proposed. These are based on the coordinate description of the corresponding point on the geometric feature for the given point, where the connecting line of the two points is the shortest path from the given point to the geometric feature to be fitted.

论文关键词:Orthogonal distance fitting,Circle fitting,Sphere fitting,Conic fitting,Orthogonal contacting condition,Singular value decomposition,Nonlinear least squares,Gauss–Newton iteration

论文评审过程:Received 16 June 2000, Accepted 12 September 2000, Available online 30 August 2001.

论文官网地址:https://doi.org/10.1016/S0031-3203(00)00152-7