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