Abstract
We introduce discrete curvatures for planar curves based on the construction of sequences of pairs of mutually dual polylines. For piecewise-regular curves consisting of a finite number of fragments of regular generalized spirals with definite (positive or negative) curvatures our discrete curvatures approximate the exact averaged curvature from below and from above. In order to derive these estimates one should provide a distance function allowing to compute the closest point on the curve for an arbitrary point on the plane.With refinement of the polylines, the averaged curvature over refined curve segments converges to the pointwise values of the curvature and, thus, we obtain a good and stable local approximation of the curvature. For the important engineering case when the curve is approximated only by the inscribed (primal) polyline and the exact distance function is not available, we provide a comparative analysis for several techniques allowing to build dual polylines and discrete curvatures and evaluate their ability to create lower and upper estimates for the averaged curvature.
References
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Articles in the same Issue
- Frontmatter
- Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory
- Discrete curvatures for planar curves based on Archimedes’ duality principle
- Predictability of the low-frequency modes of the Arctic Ocean heat content variability: a perfect model approach
- Optimal stochastic forcings for sensitivity analysis of linear dynamical systems
- On the multi-annual potential predictability of the Arctic Ocean climate state in the INM RAS climate model
Articles in the same Issue
- Frontmatter
- Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory
- Discrete curvatures for planar curves based on Archimedes’ duality principle
- Predictability of the low-frequency modes of the Arctic Ocean heat content variability: a perfect model approach
- Optimal stochastic forcings for sensitivity analysis of linear dynamical systems
- On the multi-annual potential predictability of the Arctic Ocean climate state in the INM RAS climate model