K means

On the previous answer, Rinat already gave lot of resources. But I think you need to go thru step by step for a better understanding. Check this link below:

http://aqibsaeed.github.io/2016-06-24-k-means/

Here the author explains very nicely. Also you can check it.

https://kr.mathworks.com/help/stats/kmeans.html#buefs04-X

this is the matlab default one.

SOM

For default one, check it:

https://kr.mathworks.com/help/nnet/gs/cluster-data-with-a-self-organizing-map.html

Thanks

https://www.mathworks.com/help/images/examples/color-based-segmentation-using-k-means-clustering.html

clc;

clear all;

close all;

%%%%%%%%%%%%%%%%%%%%%%%

he = imread('Tulips.jpg');

cform = makecform('srgb2lab');

lab_he = applycform(he,cform);

ab = double(lab_he(:,:,2:3));

nrows = size(ab,1);

ncols = size(ab,2);

ab = reshape(ab,nrows*ncols,2);

nColors = 3;

% repeat the clustering 3 times to avoid local minima

[cluster_idx, cluster_center] = kmeans(ab,nColors,'distance','sqEuclidean', ...

'Replicates',3);

pixel_labels = reshape(cluster_idx,nrows,ncols);

imshow(pixel_labels,[]), title('image labeled by cluster index');

figure;

segmented_images = cell(1,3);

rgb_label = repmat(pixel_labels,[1 1 3]);

for k = 1:nColors

color = he;

color(rgb_label ~= k) = 0;

segmented_images{k} = color;

end

imshow(segmented_images{1}), title('objects in cluster 1');

figure;

imshow(segmented_images{2}), title('objects in cluster 2');

figure;

imshow(segmented_images{3}), title('objects in cluster 3');

figure;

mean_cluster_value = mean(cluster_center,2);

[tmp, idx] = sort(mean_cluster_value);

blue_cluster_num = idx(1);

L = lab_he(:,:,1);

blue_idx = find(pixel_labels == blue_cluster_num);

L_blue = L(blue_idx);

is_light_blue = im2bw(L_blue,graythresh(L_blue));

nuclei_labels = repmat(uint8(0),[nrows ncols]);

nuclei_labels(blue_idx(is_light_blue==false)) = 1;

nuclei_labels = repmat(nuclei_labels,[1 1 3]);

blue_nuclei = he;

blue_nuclei(nuclei_labels ~= 1) = 0;

imshow(blue_nuclei), title('blue nuclei');