display output k-means clustering, display output clustering as a image

Question

Tomas 2014-3-13

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/121446-display-output-k-means-clustering-display-output-clustering-as-a-image

回答： Yanyu Liang 2016-11-30

采纳的回答： Dishant Arora

在 MATLAB Online 中打开

Hello,

I have a image, name image :test 3

I,map]=imread('test3','bmp');
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)

as I plot the clusters in the image, resulting

I want to draw idx and ctrs in the image.

I don't know, How do I get back image with 3 new cluster(each cluster, different color in the image)

can anyone help ?

Thanks.

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Image Analyst 2014-3-14

Sorry, I don't have the stats toolbox, which is what has kmeans.

Tomas 2014-3-14

I just want to know, how to convert ouput save in cell, back to image. Thanks.

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Answer 1

Dishant Arora 2014-3-13

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/121446-display-output-k-means-clustering-display-output-clustering-as-a-image#answer_128299

编辑：Dishant Arora 2014-3-13

在 MATLAB Online 中打开

[ I map] = imread('test3.bmp');
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);
 clusterImage = zeros(size(I));
 clusteredImage(sub2ind(size(I) , P(:,1) , P(:,2)))=IDX;
 imshow(label2rgb(clusteredImage))

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Dishant Arora 2014-3-15

编辑：Dishant Arora 2014-3-15

在 MATLAB Online 中打开

imshow(label2rgb(cluster))

Tomas 2014-3-15

Thank you very much for your help

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Answer 2

rizwan 2015-3-16

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/121446-display-output-k-means-clustering-display-output-clustering-as-a-image#answer_171536

在 MATLAB Online 中打开

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     20306   9.40619e+07
     1      2727   7.34318e+07
     1       876    7.1216e+07
     1       574   7.03212e+07
     1       410   6.98473e+07
     1       298   6.96024e+07
     1       173   6.95038e+07
     1       122   6.94633e+07
     1        65     6.945e+07
     1        45    6.9445e+07
     1        30    6.9443e+07
     1        15   6.94424e+07
     1         8   6.94422e+07
     1         3   6.94422e+07
     1         1   6.94422e+07
     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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Answer 3

Yanyu Liang 2016-11-30

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/121446-display-output-k-means-clustering-display-output-clustering-as-a-image#answer_245263

It shows how the kmeans is going at each iteration. "kmeans" implementation in matlab has two phases (you can think of it as two different approach to update assignment), so "phase" just tells if it is using first phase or second. "num" tells the number of points that change their assignment at that iteration (as you can see when it hits zero, the algorithm stops). "sum" is the objective value "kmeans" is trying to minimize.