K- Mean Clustering Algorithm Issue
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Hi Experts, I am using the following code to find clusters in my image using K - Mean [ I map] = imread('D:\MS\Research\Classification Model\Research Implementation\EnhancedImage\ROIImage.jpeg');
I = ~I;
imshow(I,map);
[m n]=size(I)
P = [];
for i=1:m
for j=1:n
if I(i,j)==1
P = [P ; i j];
end
end
end
size(P)
MON=P;
[IDX,ctrs] = kmeans(MON,3,'display', 'iter','MaxIter',500);
clusterImage = zeros(size(I));
clusteredImage(sub2ind(size(I) , P(:,1) , P(:,2)))=IDX;
imshow(label2rgb(clusteredImage))
The out put of the above code is
>> ImageEnhancement
m =
180
n =
317
ans =
20306 2
iter phase num sum
1 1 20306 9.40619e+07
2 1 2727 7.34318e+07
3 1 876 7.1216e+07
4 1 574 7.03212e+07
5 1 410 6.98473e+07
6 1 298 6.96024e+07
7 1 173 6.95038e+07
8 1 122 6.94633e+07
9 1 65 6.945e+07
10 1 45 6.9445e+07
11 1 30 6.9443e+07
12 1 15 6.94424e+07
13 1 8 6.94422e+07
14 1 3 6.94422e+07
15 1 1 6.94422e+07
16 2 0 6.94422e+07
Best total sum of distances = 6.94422e+07
Warning: Image is too big to fit on screen; displaying at 2%
Can any one explain this out put and how can i see proper out put of K- Mean???
I shall remain thank full You To
Regards
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