Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2006-02-24
Proceedings of the Third Workshop on Science with the New Generation of High Energy Gamma Experiments, p.201 (2006)
Computer Science
Computer Vision and Pattern Recognition
Scientific paper
We studied the application of the Pseudo-Zernike features as image parameters (instead of the Hillas parameters) for the discrimination between the images produced by atmospheric electromagnetic showers caused by gamma-rays and the ones produced by atmospheric electromagnetic showers caused by hadrons in the MAGIC Experiment. We used a Support Vector Machine as classification algorithm with the computed Pseudo-Zernike features as classification parameters. We implemented on a FPGA board a kernel function of the SVM and the Pseudo-Zernike features to build a third level trigger for the gamma-hadron separation task of the MAGIC Experiment.
Boinee Praveen
Cabras Giuseppe
de Angelis Alessandro
de Lotto Barbara
Dell'Orso Mauro
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