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Proceedings Paper

Curve fitting that minimizes the mean square of perpendicular distances from sample points
Author(s): Shotaro Akaho
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Paper Abstract

This paper presents a new method of curve-fitting to a set of noisy samples. In the case of fitting a curved line (or a curved surface) to given sample points, it seems natural the curve is decided so as to minimize the mean square of perpendicular distances from the sample points. However, it is difficult to get the optimal curve in the sense of this criterion. In this paper, the perpendicular distance is approximated by local linear approximation of function, and the algorithm for getting the near-optimal curve is proposed. Some simulation results are also shown.

Paper Details

Date Published: 1 December 1993
PDF: 8 pages
Proc. SPIE 2060, Vision Geometry II, (1 December 1993); doi: 10.1117/12.164998
Show Author Affiliations
Shotaro Akaho, Electrotechnical Lab. (Japan)

Published in SPIE Proceedings Vol. 2060:
Vision Geometry II
Robert A. Melter; Angela Y. Wu, Editor(s)

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