Texture recognition similar to Cascade Classifier with opencv

edit

Hi Steven,

thank you for your answer. I've tried already Haar-Cascade-Classifier for my problem. It was working quite well(created cascade classifier with about 400 images). I don't want to use template matching on µC later. This is the reason I'm looking for a classifier.

Immi, actually to get a better classification, I am guessing that using about 100 positives would be more than enough, considering you use a large set of negatives. In case of texture, the texture doesn't change that much, but the background does vary alot. You need to model that background variance.

Hi, I'll try this and reply.

For this task you don't need a cascade classifier, try out the other classifiers (if you are lazy with setting them all up, try WEKA or if you are a python guy ScikitLearn)

Doesn't it depend on how hard your texture variates?

Yeah in some kind you are right, of course you could use a cascade classifier here as well, in principle it is just a variant of AdaBoost which has the ability to reject mismatches very fast, however this may also be a weakness and another classifier, e.g. SVM, Random Forests, etc. may perform better. You should never try only one classifier! Try them all out!

Back to the original question: @Immi It will also depend much on your features you'll use, LBP for example are a popular choice for texture classification, see e.g. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5652209 , in their paper they also state that they'd make their code publicly available. Good luck

Thank you for your help, I' ll try it!

I've solved it with average color and GLCM. Thank you for your hints!

Then post your solution and accept it as the correct one, since it will help others finding solved topics.

I can't accept my answer at myself. Got to less points.