Abstract

A new method is presented to determine parameter values (knot) for data points for curve and surface generation. With four adjacent data points, a quadratic polynomial curve can be determined uniquely if the four points form a convex polygon. When the four data points do not form a convex polygon, a cubic polynomial curve with one degree of freedom is used to interpolate the four points, so that the interpolant has better shape, approximating the polygon formed by the four data points. The degree of freedom is determined by minimizing the cubic coefficient of the cubic polynomial curve. The advantages of the new method are, firstly, the knots computed have quadratic polynomial precision, i.e., if the data points are sampled from a quadratic polynomial curve, and the knots are used to construct a quadratic polynomial, it reproduces the original quadratic curve. Secondly, the new method is affine invariant, which is significant, as most parameterization methods do not have this property. Thirdly, it computes knots using a local method. Experiments show that curves constructed using knots computed by the new method have better interpolation precision than for existing methods.

Highlights

  • A fundamental problem in the fields of computer-Manuscript received: 2020-03-30; accepted: 2020-06-17 aided design, engineering, scientific computing, and computer graphics is the construction of curves and surfaces with high precision and smoothness

  • The discussion in this paper shows that computing the knots for a given set of data points can be reduced to the problem of constructing a quadratic or cubic polynomial curve

  • If the four data points do not form a convex polygon, a cubic polynomial curve with one free variable is used to interpolate the four points; the variable is determined by minimizing the cubic coefficient of the curve

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Summary

Introduction

Manuscript received: 2020-03-30; accepted: 2020-06-17 aided design, engineering, scientific computing, and computer graphics is the construction of curves and surfaces with high precision and smoothness. They require different attributes for different applications [1,2,3,4,5,6]. The chord length method is a sound parameterized method, as parameter spacings reflect the chord lengths between consecutive data points. This interpolation only works well when the parametric curve is a straight line. In terms of the approximation error, our experiments show that none of them can produce a satisfactory result

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