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function [SegLabel,EigenVectors]=discretisation(EigenVectors,nr,nc)
%
% EigenvectorsDiscrete=discretisation(EigenVectors)
%
% Input: EigenVectors = continuous Ncut vector, size = ndata x nbEigenvectors
% Output EigenvectorsDiscrete = discrete Ncut vector, size = ndata x nbEigenvectors
%
% Timothee Cour, Stella Yu, Jianbo Shi, 2004
[n,k]=size(EigenVectors);
vm = sqrt(sum(EigenVectors.*EigenVectors,2));
EigenVectors = EigenVectors./repmat(vm,1,k);
R=zeros(k);
R(:,1)=EigenVectors(1+round(rand(1)*(n-1)),:)';
c=zeros(n,1);
for j=2:k
c=c+abs(EigenVectors*R(:,j-1));
[minimum,i]=min(c);
R(:,j)=EigenVectors(i,:)';
end
lastObjectiveValue=0;
exitLoop=0;
nbIterationsDiscretisation = 0;
nbIterationsDiscretisationMax = 20;%voir
while exitLoop== 0
nbIterationsDiscretisation = nbIterationsDiscretisation + 1 ;
EigenvectorsDiscrete = discretisationEigenVectorData(EigenVectors*R);
[U,S,V] = svd(EigenvectorsDiscrete'*EigenVectors,0);
NcutValue=2*(n-trace(S));
if abs(NcutValue-lastObjectiveValue) < eps | nbIterationsDiscretisation > nbIterationsDiscretisationMax
exitLoop=1;
else
lastObjectiveValue = NcutValue;
R=V*U';
end
end
%%%%
SegLabel = zeros(nr,nc);
for j=1:size(EigenvectorsDiscrete,2),
SegLabel = SegLabel + j*reshape(EigenvectorsDiscrete(:,j),nr,nc);
end
EigenVectors = reshape(EigenVectors,nr,nc,size(EigenVectors,2));
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