Clustering the image using k means

I have detected the face and have extracted features for face such as mean ,variance ,standard deviation,
I have applied k means directly to image and have clustered,by converting to HSV,now i have to give comparison result
by applying kmeans on features extracted values on the image ,please tell how to perform this

Answers (2)

Image Analyst
Image Analyst on 23 Jan 2013
scatter() is often used to compare results by showing the clusters. Have you tried using scatter to visualize your cluster results?

2 Comments

k means on image
I = imread('');
I = im2double(I);
HSV = rgb2hsv(I);
H = HSV(:,:,1); H = H(:);
S = HSV(:,:,2); S = S(:);
V = HSV(:,:,3); V = V(:);
idx = kmeans([H S V], 4);
imshow(ind2rgb(reshape(idx, size(I,1), size(I, 2)), [0 0 1; 0 0.8 0]))
k means on values
I = imread('');
I = im2double(I);
m=mean(I(:));
va=va(I(:));
r=[m va]
idx = kmeans( );
how to apply k means for r to display image like above
Image Analyst
Image Analyst on 24 Jan 2013
Edited: Image Analyst on 24 Jan 2013
You said "I have applied k means" but it appears that you have not. I don't have the Statistics Toolbox so I can't try your code or develop any using kmeans(). All I can suggest is this Mathworks example: http://www.mathworks.com/products/demos/image/color_seg_k/ipexhistology.html

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In your example, use
kmeans(r, number_of_clusters)

5 Comments

I = imread(''); I = im2double(I); m=mean(I(:)); va=var(I(:)); r=[m va] idx = kmeans(r,2 );
in idx i get only 2 values,how that cluteres image can be image can be diplayed
You asked for 2 and got 2. Did you run the Mathworks Example to see how they can be displayed?
yes but that consists of many rows and columns ,but i have only 1row and 1 column
i have a image below
i have ectracted features
features=[m v s] for an image it is dispaled as
features=[10 12 0.9]
now as in image how to perform Image clustering
please assist
I don't have the stats toolbox so I can't try anything myself. Why don't you call tech support?

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on 23 Jan 2013

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