# please in details can anyone explain this code of K means Segmentation?

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Touhidul islam on 28 Dec 2017
Edited: Touhidul islam on 9 Jan 2018
clear all
close all
[filename,pathname] = uigetfile({'*.*';'*.bmp';'*.tif';'*.gif';'*.png'},'Pick an Image File');
[rows, columns, numberOfColorChannels] = size(I);
F = reshape(I, rows*columns, numberOfColorChannels);
K = 3; % Cluster Numbers
CENTS = F( ceil(rand(K,1)*size(F,1)) ,:); % Cluster Centers
DAL = zeros(size(F,1),K+2); % Distances and Labels
KMI = 50; % K-means Iteration
for n = 1:KMI
for i = 1:size(F,1)
for j = 1:K
DAL(i,j) = norm(F(i,:) - CENTS(j,:));
end
[Distance, CN] = min(DAL(i,1:K)); % 1:K are Distance from Cluster Centers 1:K
DAL(i,K+1) = CN; % K+1 is Cluster Label
DAL(i,K+2) = Distance; % K+2 is Minimum Distance
end
for i = 1:K
A = (DAL(:,K+1) == i); % Cluster K Points
CENTS(i,:) = mean(F(A,:)); % New Cluster Centers
if sum(isnan(CENTS(:))) ~= 0 % If CENTS(i,:) Is Nan Then Replace It With Random Point
NC = find(isnan(CENTS(:,1)) == 1); % Find Nan Centers
for Ind = 1:size(NC,1)
CENTS(NC(Ind),:) = F(randi(size(F,1)),:);
end
end
end
end
X = zeros(size(F));
for i = 1:K
end idx = find(DAL(:,K+1) == i);
X(idx,:) = repmat(CENTS(i,:),size(idx,1),1);
end
##### 2 CommentsShowHide 1 older comment
Touhidul islam on 28 Dec 2017
sir , i have done all the necessary things you had asked me to do.

Bernhard Suhm on 5 Jan 2018
You need to provide some more context, what are you trying to accomplish? Right now, this feels like a coding puzzle. By my interpretation, this code clusters all the pixes of the input image into 3 clusters (running k-means KMI times), and then replaces each pixel by its cluster.

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