Machine Learning Techniques for Vehicle Detection

The traffic surveillance system is a type of intelligent control. Traffic control provides solutions to most problems faced by people. It helps monitor, detect congestion and accidents. As science evolved, it became possible using video surveillance. Video the economical option that does not involve high costs or changes in infrastructure. Vehicle detection one main parts system. In this paper, vehicles will be detected two different artificial intelligence methods (the YOLO method HAAR cascade classifier method). first smarter than second method, both them contain machine learning. processing step read video. Then vehicle algorithms are applied ways. comparison between depends on results find effective applicable method. After implementing methods, were obtained YOLO, accuracy 91.31% error rate 8.69%, time 10 sec. for XML (HAAR method) 86.9%, quality completeness 90.9%, 13%, 17 Thus, we conclude has better Index Terms— Artificial Intelligence, Machine Learning, Detection, Yolo Method.