A new deterministic heuristic knots placement for B-Spline approximation

D. Michel and A. Zidna

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 186, issue C, 91-102

Abstract: In this paper, we propose an adaptive knot placement algorithm for B-Spline curve approximation to dense and noisy 2D data points. The proposed algorithm is based on a heuristic rule for knot placement. It consists in constructing a distribution knot function by blending geometric criteria such as discrete derivatives, discrete angular variations and curvature. It has been successfully compared to three well known methods for approximating various noisy functions and sets of data in handwriting context.

Keywords: Dense and noisy data; B-Spline approximation; Knot placement; Discrete derivatives; Discrete angular variation; Curvature; Handwriting compression (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:186:y:2021:i:c:p:91-102

DOI: 10.1016/j.matcom.2020.07.021

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