Arc-Length Based Curvature Estimator

Authors:
Thomas Lewiner;Joao D. Gomes Jr.;Helio Lopes;Marcos Craizer
Affiliations:
PUC-Rio, Rio de Janeiro, Brazil/ INRIA, Sophia Antipolis, France;PUC-Rio, Rio de Janeiro, Brazil;PUC-Rio, Rio de Janeiro, Brazil;PUC-Rio, Rio de Janeiro, Brazil
Venue:
SIBGRAPI '04 Proceedings of the Computer Graphics and Image Processing, XVII Brazilian Symposium
Year:
2004

Citing 0
Cited 4

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Abstract

Many applications of geometry processing and computer vision relies on geometric properties of curves, particularly their curvature. Several methods have been proposed to estimate the curvature of a planar curve, most of them for curves in digital spaces. This work proposes a new method for curvature estimation based on weighted least square fitting and local arc-length approximation. Convergence analysis of this method and noise impact on the estimator accuracy are given. Numerical robustness issues are addressed with practical solutions. The implementation of the method is compared to other curvature estimation methods.