Video-based vehicle tracking and capturing system for expressway tollgates

In order to reduce the noise impacts in front of the camera and improve the vehicle capturing precision in expressway tollgate scenes, an efficient and flexible judgment framework for vehicle capture was proposed. Specifically, through the analyses of the common motion detection methods, an improved frame difference approach based on motion history images was applied to the framework to increase the motion detection sensitivity. To relieve the calculation complexity, a fast detection algorithm for searching vehicle rectangular region was given. Furthermore, the spatio-temporal rules for vehicle capture judgment were defined, as a result, the judgment framework was formed. In addition, parallel vehicle capturing experiments were conducted on multiple lanes under varied illumination in real time. The experiment result shows that using the proposed framework, the average precision for a 5.5 h test sequence is up to 87.8%, and it is able to resist vehicle and bar movement noises and luminance variation to improve the vehicle capturing precision.