Image segmentation using Otsu thresholding 1.0

IDX = OTSU(I,N) segments the image I into N classes by means of Otsu's N-thresholding method. OTSU returns an array IDX containing the cluster indices (from 1 to N) of each point. IDX = OTSU(I) uses two classes (N=2, default value). [IDX,sep] = OTSU(I,N) also returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with data having less than N values, whereas one (optimal value) is obtained only with N-valued arrays.If I is an RGB image, a Karhunen-Loeve transform is first performed on the three R,G,B channels. The segmentation is then carried out on the image component that contains most of the energy. Example:--------- load clown subplot(221) X = ind2gray(X,map); imshow(X) title('Original','FontWeight','bold') for n = 2:4 IDX = otsu(X,n); subplot(2,2,n) imagesc(IDX), axis image off title(['n = ' int2str(n)],'FontWeight','bold') end ------See also:http://www.biomecardio.com/matlab/otsu.html

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Arrays,  Carried,  Channels,  Nvalued,  Optimal,  Performed,  Segmentation,  Transform
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