Semester assignments for the course "Digital Image Processing" of THMMY in AUTH university.
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function clusterIdx = mySpectralClustering (anAffinityMat, k)
%Implementation of spectral clustering
% Usage clusterIdx = mySpectralClustering (anAffinityMat, k), where:
% Inputs
% - anAffinityMat is a rectagular, symmetrical affinity matrix
% representation of an image
% - k is the desired number of clusters
% Output
% - clusterIdx is a vector storing the cluster Id of each node
if ~issymmetric(anAffinityMat)
error('The affinity matrix provided is not symmetric.');
end
L = diag(sum(anAffinityMat, 2)) - anAffinityMat;
[eigenvectorsMatrix, ~] = eigs(double(L), k, 'sm');
clusterIdx = kmeans(eigenvectorsMatrix, k);
end