Public and Private Vehicle Quantification and Classification using Vehicle Detection and Recognition
Leonard U. Ambata, Isabel Angela P. del Castillo, Jeremiah Rod H. Jacinto, Cellix Mark T. Santos · 2019
Traffic congestion in the Philippines is diverse consisting public and private vehicles. One approach of this is to design a system that can count, detect, recognize, and classify public and private vehicles from a surveillance video. This research introduces the development of the said system, to be used as a statistical data for implementing traffic rules. The dataset the researchers used consists of 13,600 images: 10,880 images for training and 2,720 images for testing. These were obtained from a gas station video source, for the vehicles frequently passing though in a gas station. The researchers used an algorithm called Convolutional Neural Network for the detecting and classifying vehicles.