Naive Bayes for image processing
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Hi, I'm very new to matlab and now I need to implement skin detection using Baysian classification. I read a bit of tutorial for NaiveBayes and came out with the following:
P=imread('H:\skin.tif');
nbGau= NaiveBayes.fit(P(:,1:2), species);
nbGauClass= nbGau.predict(P(:,1:2));
is it the right way for training and sampling? if I'm still correct, how can I get "species" value?
Please inspire me of how to implement Bayesian classification in image processing... Thanks so much in advance!
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Image Analyst
on 1 Oct 2012
Edited: Image Analyst
on 1 Oct 2012
What toolbox is all this stuff in? Can you add it to the Products below? It's not in the Image Processing Toolbox.
Answers (1)
Kapil Nagwanshi
on 1 Oct 2012
Edited: Kapil Nagwanshi
on 1 Oct 2012
I think you are going through
1 load fisheriris
2 O1 = NaiveBayes.fit(meas,species);
3 C1 = O1.predict(meas);
4 cMat1 = confusionmat(species,C1)
The first line loads a double 2d matrix called as meas and also a cell of 150x1 displaying (See RHS workspace box) 'setosa' ... ... in your case i dont know what you want to classify but the steps you want to try must alter to the standard way. see
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