CODEWITHSUNDEEP
matlabmachine-learningclassificationbayesian
bims
bims

Reputation: 33

Bayes classification in matlab

I have 50 images and created a database of the green channel of each image by separating them into two classes (Skin and wound) and storing the their respective green channel value.

Also, I have 1600 wound pixel values and 3000 skin pixel values.

Now I have to use bayes classification in matlab to classify the skin and wound pixels in a new (test) image using the data base that I have. I have tried the in-built command diaglinear but results are poor resulting in lot of misclassification.

Also, I dont know if it's a normal distribution or not so can't use gaussian estimation for finding the conditional probability density function for the data.

Is there any way to perform pixel wise classification?

If there is any part of the question that is unclear, please ask.

I'm looking for help. Thanks in advance.

Upvotes: 3

Views: 2800

Answers (1)

santonsh
santonsh

Reputation: 66

If you realy want to use pixel wise classification (quite simple, but why not?) try exploring pixel value distributions with hist()/imhist(). It might give you a clue about a gaussianity... Second, you might fit your values to the some appropriate curves (gaussians?) manually with fit() if you have curve fitting toolbox (or again do it manualy). Then multiply the curves by probabilities of the wound/skin if you like it to be MAP classifier, and finally find their intersection. Voela! you have your descition value V. if Xi skin else -> wound

Upvotes: 2

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