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Proceedings Paper

Incremental matrix orthogonalization with an application to curve fitting
Author(s): Matthew Harker; Paul O'Leary; Paul Zsombor-Murray
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Paper Abstract

A new method for fitting implicit curves to scattered data is proposed. The method is based on orthogonal matrix projections and singular value decomposition. The incremental aspect of the algorithm deals with each order of data individually in an incrementing manner, whereby a matrix approximation procedure is applied at each level. This determines the fit quality at each step, and hence provides co-linearity detection of each polynomial order. The best implicit polynomial fit of minimal order is provided, which essentially combines object identification and classification with object fitting.

Paper Details

Date Published: 11 March 2005
PDF: 8 pages
Proc. SPIE 5674, Computational Imaging III, (11 March 2005); doi: 10.1117/12.586499
Show Author Affiliations
Matthew Harker, Institute for Automation, Univ. of Leoben (Austria)
Paul O'Leary, Institute for Automation, Univ. of Leoben (Austria)
Paul Zsombor-Murray, Ctr. for Intelligent Machines, McGill Univ. (Canada)


Published in SPIE Proceedings Vol. 5674:
Computational Imaging III
Charles A. Bouman; Eric L. Miller, Editor(s)

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