Video-Based Vehicle Flow Detection Algorithm

In recent years, urban traffic congestion has become increasingly serious. More and more scholars have begun to study about intelligent transportation system, and the real-time detection of vehicle flow is one of the most valuable research issues. In this paper, we propose an algorithm called VFDV (Vehicle Flow Detection algorithm based on Video) that can detect vehicle flow in real time. This algorithm uses road video surveillance as the source data and extracts valid images from it to detect vehicle flow. Different from the traditional methods that use vehicle recognition method to detect vehicle flow, algorithm VFDV uses a classification algorithm to detect vehicle flow. Compared with traditional algorithms, our algorithm achieves higher accuracy. In the verification phase, the video taken at the real intersection is used as the data source. Experiments on real dataset are designed to verify the effectiveness and superiority of the proposed algorithm.