conicfit (version 1.0.4)

fit.conicLMA: Fitting a conic to a given set of points (Implicit method)

Description

fit.conicLMA fits a conic to a given set of points (Implicit method) using algebraic parameters. Conic: Ax^2 + Bxy + Cy^2 +Dx + Ey + F = 0

Usage

fit.conicLMA(XY, ParAini, LambdaIni, epsilonP = 1e-10, epsilonF = 1e-13,
IterMAX = 2e+06)

Arguments

XY

array of sample data

ParAini

initial parameter vector c(A,B,C,D,E,F)

LambdaIni

initial value of the control parameter Lambda

epsilonP

tolerance (small threshold)

epsilonF

tolerance (small threshold)

IterMAX

maximum number of (main) iterations, usually 10-20 will suffice

Value

list(ParA, RSS, iters

list with algebraic parameters (Center(1:2), Axes(1:2), Angle), Residual Sum of Squares and number of iterations

Source

Nikolai Chernov, 2014 Fitting ellipses, circles, and lines by least squares http://people.cas.uab.edu/~mosya/cl/ N. Chernov, Q. Huang, and H. Ma, 2014 Fitting quadratic curves to data points British Journal of Mathematics & Computer Science, 4, 33-60. N. Chernov and H. Ma, 2011 Least squares fitting of quadratic curves and surfaces In: Computer Vision, Editor S. R. Yoshida, Nova Science Publishers; pp. 285-302.

References

Nikolai Chernov, 2014 Fitting ellipses, circles, and lines by least squares http://people.cas.uab.edu/~mosya/cl/

N. Chernov, Q. Huang, and H. Ma, 2014 Fitting quadratic curves to data points British Journal of Mathematics & Computer Science, 4, 33-60.

N. Chernov and H. Ma, 2011 Least squares fitting of quadratic curves and surfaces In: Computer Vision, Editor S. R. Yoshida, Nova Science Publishers; pp. 285-302.

Examples

XY <- matrix(c(1,7,2,6,5,8,7,7,9,5,3,7,6,2,8,4),8,2,byrow=TRUE)
ParAini <- matrix(c(0.2500,0, 1.0000, 0, 0, -1.0000),ncol=1)
LambdaIni=0.1
fit.conicLMA(XY,ParAini,LambdaIni)