K- Mean Clustering Algorithm Issue

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