I am trying to train a cascade classifier with matlab and c++. I am trying to detect optic disc in retinal fundus images. number for positive samples i have used are around 12000(after flipping) and negative samples are 10000. Max hit rate is 0.995 and false alarm rate is 0.1. I trained a classifier using matlab for 40 stages using haar and one with hog features. Testin for one image takes hours and returns very bad results. if anyone can tell me what i am doing wrong it would be very help full. Even if i reduce the number of stages to 20 it still takes hours to test.
PS:- Dimensions of positive and negative images is roughy around 800x1200. C++ classifier is not yet trained.Its been 15 days. May be i will get results from c++ when hell freezes over.
Thanks.