www.pudn.com > Ms_segmenter.rar > Fit_spline.m

function Dense_pts = Fit_spline (Pts) 
 
Xdata = Pts(1, :); 
Ydata = Pts(2, :); 
 
% making splines separately for X and Y, but with common parameter 
Length = 0; 
Param(1) = Length; 
for i=1:length(Xdata)-1 
	Length = Length + norm(Pts(:, i+1) - Pts(:, i)); 
	Param(i+1) = Length; 
end 
 
% sampling at a dense set of points 
Gridpts = [min(Param):0.1:max(Param)]; 
Xspline = round(spline(Param, Xdata, Gridpts)); 
Yspline = round(spline(Param, Ydata, Gridpts)); 
 
% if not sufficiently dense, adjusting those 
k = 0;  Dense_pts = zeros(2, 0); 
for i=1:length(Xspline)-1 
	if max(abs(Xspline(i+1)-Xspline(i)), abs(Yspline(i+1)-Yspline(i))) > 1 
		for j=0:abs(Xspline(i+1)-Xspline(i)) 
			k = k+1; 
			Dense_pts(:, k) = [Xspline(i) + j*sign(Xspline(i+1)-Xspline(i)); ... 
				Yspline(i)]; 
		end 
		for j=0:abs(Yspline(i+1)-Yspline(i)) 
			k = k+1; 
			Dense_pts(:, k) = [Xspline(i+1); ... 
				Yspline(i) + j*sign(Yspline(i+1)-Yspline(i))]; 
		end 
	 else 
	 	k = k+1; 
	 	Dense_pts(:, k) = [Xspline(i); Yspline(i)]; 
	end 
end