Curve approximation by G1 arc splines with a limited number of types of curvature and length

被引:2
|
作者
Mizutani, Keisuke
Kawaguchi, Ken'ichi
机构
关键词
Arc spline; Approximation; Optimization; Clustering; DISCRETE-DATA;
D O I
10.1016/j.cagd.2021.102036
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
A method for approximating planar curves by G(1) continuous arc splines with a limited number of types of curvatures and lengths, named k-arc splines, is proposed. A k-arc spline is a particular arc spline, and it has only k types of arcs less than the total number of segments. Due to this property, k-arc splines require discrete variables that relate segments and k types of arcs for representation. Therefore k-arc spline approximation problems must deal with discrete variables in contrast to general arc spline approximation problems. The authors present a method to appropriately estimate these variables from curvature values of a target curve. The proposed method enables a formulation of the approximation problem as a continuous optimization problem that conventional optimization algorithms can solve efficiently. The estimation method also provides a suitable initial solution for the algorithms. Some examples to show the broad applicability of the proposed algorithm are shown. (C) 2021 Elsevier B.V. All rights reserved.
引用
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页数:14
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