| fit.conicLMA {conicfit} | R Documentation |
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 |
Author(s)
Jose Gama
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)