kmeans clustering is used for Image Compression. In this matlab program, the feature vectors are simply the N X N nonoverlapping blocks of pixels in the image. Like a scalar quantizer, a vector quantizer has a quantization levels called codevectors and the set of K such codevectors is called codebook of size K.
Kmeans clustering is an iterative process in which the codevectors are refined every stage by computing the centroid of the input vectors which belong to the respective cluster.
1.5.0.0  A small bug is fixed. 

1.4.0.0  I have revamped the code completely to make it more efficient(run Faster). I have rectified all the previous bugs. Feel free to contact me at my email address. See ya!! 

1.3.0.0  I have revamped the code completely to make it more efficient and hence run faster. The bugs in the previous version are fixed and hopefully its bugfree now. See ya!! :) 

1.2.0.0  This file solves the issues with different dimensions of the images and also prints the output in a userfriendly manner. 

1.1.0.0  The file I uploaded previously will fail to work for Images of different dimensions, since it was not generalized for all the dimensions. This updated file contains the instructions for working on different dimensions of Images. 
Create scripts with code, output, and formatted text in a single executable document.
sanju tom (view profile)
sir , I want document for this project
amir (view profile)
Mayuri (view profile)
I want to compress a grayscale image using vector quantization. I have not understood how you have generated the codebook. Will you please explain me the steps for generation of the same in your code
Edwin (view profile)
Hello, thanks for your sharing.
However, when I tried to test this code, i got some errors pposted below...my input image is a 181*217 png image...would you please help me to solve this problem?
Thanks for your help in advanced!
Attempted to access I1(1,2.41421); index must be a positive integer or logical.
Error in ==> K_MEANS_PREPROCESSING at 18
s((L^0.5*size(I1,2))*(i1)+L*(j1)+(L^0.5)*(k1)+l)=I1(sqrt(L)*(i1)+k, sqrt(L)*(j1)+l);
Error in ==> Image_kmeans_main at 72
I_re=K_MEANS_PREPROCESSING(Img1,L,K);
Vinay Kumar Tadepalli (view profile)
Hey Nidhi, Thanks for all the comments. I have updated the file again and this time i have tested for different images and it is working fine. You need to supply input parameters such as L & K for the program. First try with L=4 and K=16. This will execute in approx. 50 sec. Then you can try for other combinations.
Nidhi (view profile)
Thanks for your support. This new code doesnot give the error I got earlier, but the program is busy in its operation and finally it says "elapsed time". The program works for about 21 min approx.
Hope you will help me in resolving this issue.
Thanks,
Nidhi
Neha (view profile)
resolved with the above query.. m new to MATLAB.. i need k mean clustering technique to apply on my images for my project having deadline 15th july.. plzz help me for classifying my 255*255 grayscale satellite images into 3 clusters..
will be very grateful to u..
looking for possitive feedback in anticipation...
Nidhi (view profile)
In fact I tried using the original code with a 512*512 image but it too gets hanged or matlab shows status as busy and then nothing happens.
Thanks
Nidhi
Vinay Kumar Tadepalli (view profile)
Hey, Thanks for the feedback. Actually, when i wrote the code, i have used 512 X 512 image and didnt generalize it for all dimensions. I am pasting a new code here which should work for all dimensions of images.

clc;
clear all;
tic;
I1=imread('C:\Users\as\Documents\MATLAB\Test Images\1.gif');
%% Creating Ldimension vectors from the Image.
% For an Image, L is an integer power of 2.
s=zeros(1,size(I1,1)*size(I1,2));
L=4;
for i=1:size(I1,1)/sqrt(L)
for j=1:size(I1,2)/sqrt(L)
for k=1:sqrt(L)
for l=1:sqrt(L)
s((L^0.5*size(I1,2))*(i1)+L*(j1)+(L^0.5)*(k1)+l)=I1(sqrt(L)*(i1)+k, sqrt(L)*(j1)+l);
end
end
end
end
imshow(I1);
K=256; % K is the Codebook Size.
[codebook,ClusterNum]=kmeans_clustering(s,L,K);
% Reconstructing the Image using the Codebook vectors (Cluster Centres).
s_re=zeros(1,length(ClusterNum)*L);
for i=1:length(ClusterNum)
s_re(L*(i1)+1:L*i)=codebook(ClusterNum(i)).samples;
end
I_re=zeros(size(I1));
for i=1:size(I1,1)/sqrt(L)
for j=1:size(I1,2)/sqrt(L)
for k=1:sqrt(L)
for l=1:sqrt(L)
I_re(sqrt(L)*(i1)+k, sqrt(L)*(j1)+l)=s_re((L^0.5*size(I1,2))*(i1)+L*(j1)+(L^0.5)*(k1)+l);
end
end
end
end
clear s s_re;
figure, imshow(uint8(I_re));
toc;
Nidhi (view profile)
When I use a .jpg file it says :
"??? Attempted to access I1(1,247); index out of bounds because size(I1)=[185,246].
Error in ==> image_kmeans at 17
s((L^0.5*512)*(i1)+L*(j1)+(L^0.5)*(k1)+l)=I1(sqrt(L)*(i1)+k,
sqrt(L)*(j1)+l); "
I tried changing the size of the image but still it gives the same error. Only the coordinate or pixel value of out of bound changes.
Can you pl. tell me the size of image which I should use.
Thanks,
Nidhi