最小二乘椭圆拟合matlab代码实现

function Re = EllipseDirectFit(XY);
%  Direct ellipse fit, proposed in article
%    A. W. Fitzgibbon, M. Pilu, R. B. Fisher
%     "Direct Least Squares Fitting of Ellipses"
%     IEEE Trans. PAMI, Vol. 21, pages 476-480 (1999)
%
%  Our code is based on a numerically stable version
%  of this fit published by R. Halir and J. Flusser
%
%     Input:  XY(n,2) is the array of coordinates of n points x(i)=XY(i,1), y(i)=XY(i,2)
%
%     Output: A = [a b c d e f]' is the vector of algebraic 
%             parameters of the fitting ellipse:
%             ax^2 + bxy + cy^2 +dx + ey + f = 0
%             the vector A is normed, so that ||A||=1
%
%  This is a fast non-iterative ellipse fit.
%
%  It returns ellipses only, even if points are
%  better approximated by a hyperbola.
%  It is somewhat biased toward smaller ellipses.
%
centroid = mean(XY) ; % the centroid of the data set
warning off;
D1 = [(XY(:,1)-centroid(1)).^2, (XY(:,1)-centroid(1)).*(XY(:,2)-centroid(2)),...
      (XY(:,2)-centroid(2)).^2];
D2 = [XY(:,1)-centroid(1), XY(:,2)-centroid(2), ones(size(XY,1),1)];
S1 = D1'*D1;
S2 = D1'*D2;
S3 = D2'*D2;
T = -inv(S3)*S2';
M = S1 + S2*T;
M = [M(3,:)./2; -M(2,:); M(1,:)./2];
[evec,eval] = eig(M);
cond = 4*evec(1,:).*evec(3,:)-evec(2,:).^2;
A1 = evec(:,find(cond>0));
A = [A1; T*A1];
A4 = A(4)-2*A(1)*centroid(1)-A(2)*centroid(2);
A5 = A(5)-2*A(3)*centroid(2)-A(2)*centroid(1);
A6 = A(6)+A(1)*centroid(1)^2+A(3)*centroid(2)^2+...
     A(2)*centroid(1)*centroid(2)-A(4)*centroid(1)-A(5)*centroid(2);
A(4) = A4;  A(5) = A5;  A(6) = A6;
A = A/norm(A);
Re=A;
a=A(1);
b=A(2);
c=A(3);
d=A(4);
e=A(5);
f=A(6);
eq0= 'a*x^2 + b*x*y + c*y^2 +d*x + e*y + f ';
 eq0=@(x,y) a*x^2 + b*x*y + c*y^2 +d*x + e*y + f;
 h=ezplot(eq0,[1,128,1,128]);
set(h,'Color','y');
end  %  EllipseDirectFit