Curve Reconstruction Algorithm Based on Discrete Data Points and Normal Vectors
Curve Reconstruction Algorithm Based on Discrete Data Points and Normal Vectors作者机构：Department of Mathematics Dalian University of Technology
出 版 物：《Journal of Mathematical Research with Applications》 (数学研究及应用(英文))
年 卷 期：2020年第40卷第1期
页 面：87-100页
核心收录：
学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 08[工学] 080203[工学-机械设计及理论] 081304[工学-建筑技术科学] 0802[工学-机械工程] 0813[工学-建筑学] 080201[工学-机械制造及其自动化]
基 金：Supported by the National Natural Science Foundation of China(Nos.11871137 11572081) the Program for Liaoning Innovation Talents in University(No.LCR2018001)
主 题：curve reconstruction curve fitting normal vector B-spline dominant point
摘 要：This paper presents a curve reconstruction algorithm based on discrete data points and normal vectors using B-splines. The proposed algorithm has been improved in three steps:parameterization of the discrete data points with tangent vectors, the B-spline knot vector determination by the selected dominant points based on normal vectors, and the determination of the weight to balancing the two errors of the data points and normal vectors in fitting ***, we transform the B-spline fitting problem into three sub-problems, and can obtain the B-spline curve adaptively. Compared with the usual fitting method which is based on dominant points selected only by data points, the B-spline curves reconstructed by our approach can retain better geometric shape of the original curves when the given data set contains high strength noises.
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