Clustering the image using k means

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nkumar
nkumar am 23 Jan. 2013
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

Antworten (2)

Image Analyst
Image Analyst am 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 Kommentare
nkumar
nkumar am 24 Jan. 2013
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 am 24 Jan. 2013
Bearbeitet: Image Analyst am 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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Thorsten
Thorsten am 24 Jan. 2013
In your example, use
kmeans(r, number_of_clusters)
  5 Kommentare
nkumar
nkumar am 3 Feb. 2013
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
Image Analyst
Image Analyst am 3 Feb. 2013
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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