Curvature Estimation for Discrete Curves based on Auto-adaptive Masks of Convolution
Abstract
We propose a method that we call auto-adaptive convolution which extends the classical notion of convolution in pictures analysis to function analysis on a discrete set. We define an averaging kernel which takes into account the local geometry of a discrete shape and adapts itself to the curvature. Its defining property is to be local and to follow a normal law on discrete lines of any slope. We used it together with classical differentiation masks to estimate first and second derivatives and give a curvature estimator of discrete functions.
Domains
Discrete Mathematics [cs.DM]Origin | Files produced by the author(s) |
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