Tracking and counting of vehicles for flow analysis from urban traffic videos

Among the major problems faced by urban centers there is traffic congestion. This problem comes from the growing number of vehicles on the streets and has already become the subject of several researches seeking for solutions to it. Among the mechanisms that allow congestion reduction is traffic control, which requires metrics that enable traffic analysis in real time. To determine the flow of vehicles the widely used mechanism is the counting of occurrence of vehicles on a street, which is usually performed from sensors (e.g. magnetic or thermal). However, these approaches have a rather high installation and maintenance difficulty. Thus, the objective of this paper is to present a mechanism capable of counting from video images. To accomplish this task it is used image processing resources that do not require large computational power, thus allowing the mechanism to be easily coupled to common transit systems. The result obtained has an accuracy of more than 90 % in videos of urban traffic cameras.