K Means Algorithm with the application to image compression
by
Jason Rebello
25 Jul 2013
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


Contact us