CircleFitByTaubin: Algebraic circle fit (Taubin method)

In conicfit: Algorithms for Fitting Circles, Ellipses and Conics Based on the Work by Prof. Nikolai Chernov

Description

CircleFitByTaubin applies the simple algebraic circle fit (Taubin method)

Usage

CircleFitByTaubin(XY)

Arguments

XY	array of sample data

Value

vector(a, b, R)

vector with the values for the circle: center (a,b) and radius R

Author(s)

Jose Gama

Source

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

Nikolai Chernov, 2010 Circular and linear regression: Fitting circles and lines by least squares Chapman & Hall/CRC, Monographs on Statistics and Applied Probability, Volume 117

References

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

Nikolai Chernov, 2010 Circular and linear regression: Fitting circles and lines by least squares Chapman & Hall/CRC, Monographs on Statistics and Applied Probability, Volume 117

Examples

xy<-calculateCircle(0,0,200,50,randomDist=TRUE,noiseFun=function(x) (x+rnorm(1,mean=0,sd=50)))
plot(xy[,1],xy[,2],xlim=c(-250,250),ylim=c(-250,250));par(new=TRUE)
c1 <- CircleFitByTaubin(xy)
xyc1<-calculateCircle(c1[1],c1[2],c1[3])
plot(xyc1[,1],xyc1[,2],xlim=c(-250,250),ylim=c(-250,250),col='red',type='l');par(new=TRUE)

Example output

Loading required package: pracma
Loading required package: geigen

conicfit documentation built on May 2, 2019, 5:01 p.m.