Naive Bayes for image processing

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!

[Image Analyst]

What toolbox is all this stuff in? Can you add it to the Products below? It's not in the Image Processing Toolbox.

Answer 1

[Kapil Nagwanshi]

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

http://www.mathworks.in/help/stats/naivebayes.fit.html