how to choose specific color to display when using kmean clustering color segmentation?

Question

badrul hisham 2016-4-14

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/278939-how-to-choose-specific-color-to-display-when-using-kmean-clustering-color-segmentation

评论： Image Analyst 2017-4-18

hi, i am learning how to segment colors by using kmean clustering just like the example in matlab 2015a. but each time i run the codes, the colors that i want are in different clusters. for example, for the first run,it will display that yellow is in cluster 1 and blue is in cluster 2. but when i run it again, they will switch to different cluster. how to make the yellow and blue is in specific clusters even if i run it again and again? please help me. thanks in advance

 [FileName,PathName] = uigetfile('*.jpg','Select the MATLAB code file');
 he1= imread(FileName);
 cform = makecform('srgb2lab');
 lab_he = applycform(he1,cform);
 figure (2)
 imshow (lab_he)
 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);
 figure (3)
 imshow(pixel_labels,[]), title('image labeled by cluster index');
 segmented_images = cell(1,3);
 rgb_label = repmat(pixel_labels,[1 1 3]);
 for k = 1:nColors
     color = he1;
     color(rgb_label ~= k) = 0;
     segmented_images{k} = color;
 end
 figure (4)
 imshow(segmented_images{1}), title('objects in cluster 1');
 figure (5)
 imshow(segmented_images{2}), title('objects in cluster 2');
 figure (6)
 imshow(segmented_images{3}), title('objects in cluster 3');

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Answer 1

Image Analyst 2016-5-7

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https://ww2.mathworks.cn/matlabcentral/answers/278939-how-to-choose-specific-color-to-display-when-using-kmean-clustering-color-segmentation#answer_221162

You have to pick your class colors that you want the classes displayed in. Then for each cluster, you have to find the mean color (centroid) of all the colors in the cluster. Then see which class color is closest (Euclidean distance) to your cluster color.