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function [centers,label,post,d2]=find_textons(fv,ncenters,centers_in,n_iter);
% [centers,label,post,d2]=find_textons(FIw,ncenters,centers_in,n_iter);
%
% find textons using kmeans for windowed portion FIw of filtered image
%
% to start with centers pulled randomly from image, set centers_in=[]
[N1,N2] =size(fv);
% take centers randomly from within image
if isempty(centers_in)
rndnum=1+floor(N1*rand(1,ncenters));
centers_in=fv(rndnum,:);
end
options = foptions;
options(1)=1; % Prints out error values.
options(5) = 0;
if nargin<4
n_iter=15;
end
options(14) = n_iter; % Number of iterations.
[centers,options,d2,post]=kmeans2(centers_in,fv,options);
% retrieve cluster number assigned to each feature vector
[minval,label]=min(d2,[],2);
h = hist(label(:),[1:max(label(:))]);
a = h>0;
a = cumsum(a);
[nr,nc] = size(label);
label = reshape(a(label(:)),nr,nc);
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