Color quantization of an image using K-means clustering (using RGB features)

Question

Is it possible to clustering for RGB + spatial features of images with matlab?

NOTE: I want to use kmeans for clustering.

In fact basicly i want to do one thing, i want to get this image

from this

Answer 1

I think you are looking for color quantization.

[imgQ,map]= rgb2ind(img,4,'nodither'); %change this 4 to the number of desired colors
                                       %in quantized image
imshow(imgQ,map);

Result:

Using kmeans :

%img is the original image

imgVec=[reshape(img(:,:,1),[],1) reshape(img(:,:,2),[],1) reshape(img(:,:,3),[],1)];
[imgVecQ,imgVecC]=kmeans(double(imgVec),4); %4 colors
imgVecQK=pdist2(imgVec,imgVecC); %choosing the closest centroid to each pixel, 
[~,indMin]=min(imgVecQK,[],2);   %avoiding double for loop

imgVecNewQ=imgVecC(indMin,:);  %quantizing
imgNewQ=img;
imgNewQ(:,:,1)=reshape(imgVecNewQ(:,1),size(img(:,:,1))); %arranging back into image
imgNewQ(:,:,2)=reshape(imgVecNewQ(:,2),size(img(:,:,1)));
imgNewQ(:,:,3)=reshape(imgVecNewQ(:,3),size(img(:,:,1)));

imshow(img)
figure,imshow(imgNewQ,[]);

Result of kmeans :

If you want to add distance constraint to kmeans, the code will be slightly different. Basically, you need to concatenate pixel coordinates of corresponding pixel vales too. But remember, while assigning nearest centroid to each pixel, assign only the color i.e. the first 3 dimensions, not the last 2. That doesn't make sense, obviously. The code is very similar to the previous, please note the changes and understand them.

[col,row]=meshgrid(1:size(img,2),1:size(img,1));
imgVec=[reshape(img(:,:,1),[],1) reshape(img(:,:,2),[],1) reshape(img(:,:,3),[],1) row(:)   col(:)];
[imgVecQ,imgVecC]=kmeans(double(imgVec),4); %4 colors
imgVecQK=pdist2(imgVec(:,1:3),imgVecC(:,1:3));

[~,indMin]=min(imgVecQK,[],2);
imgVecNewQ=imgVecC(indMin,1:3);  %quantizing
imgNewQ=img;
imgNewQ(:,:,1)=reshape(imgVecNewQ(:,1),size(img(:,:,1))); %arranging back into image
imgNewQ(:,:,2)=reshape(imgVecNewQ(:,2),size(img(:,:,1)));
imgNewQ(:,:,3)=reshape(imgVecNewQ(:,3),size(img(:,:,1)));

imshow(img)
figure,imshow(imgNewQ,[]);

Result of kmeans with distance constraint: