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K Means Algorithm with the application to image compression

K Means Algorithm with the application to image compression

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This program uses the K means clustering algorithm to group the pixels in an image

computeNewCentroids(X, idx, K)
function centroids = computeNewCentroids(X, idx, K)

% computeNewCentroids computes the new centroids of each cluster based on
% the mean value of the all the points belonging to that cluster.

% Initialize variables
[m n] = size(X);
centroids = zeros(K, n);

for i=1:K
    temp = find(idx==i);
    Xtemp = X(temp,:); % Get all points belonging to that cluster
    centroids(i,:) = (sum(Xtemp,1))./length(Xtemp); % Assign new centroid based on mean
end

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