Classification methods for magic telescope images on a pixel-by-pixel base

The problem of identifying gamma ray events out of charged cosmic ray background (so called hadrons) in Cherenkov telescopes is one of the key problems in VHE gamma ray astronomy. In this contribution, we present a novel approach to this problem by implementing different classifiers relying on the information of each pixel of the camera of a Cherenkov telescope, rather than using common Hillas parameter analysis. Separation between gamma-like and hadron-like events is tested by using Monte Carlo data samples of both types of events.