Detecting and Tracking Vehicles at Local Region by using Segmented Regions Information
Dae-Ho Lee, Young-Tae Park · Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong · 2007
The novel vision-based scheme for real-time extracting traffic parameters is proposed in this paper. Detecting and tracking of vehicle is processed at local region installed by operator. Local region is divided to segmented regions by edge and frame difference, and the segmented regions are classified into vehicle, road, shadow and headlight by statistical and geometrical features. Vehicle is detected by the result of the classification. Traffic parameters such as velocity, length, occupancy and distance are estimated by tracking using template matching at local region. Because background image are not used, it is possible to utilize under various conditions such as weather, time slots and locations. It is performed well with 90.16% detection rate in various databases. If direction, angle and iris are fitted to operating conditions, we are looking forward to using as the core of traffic monitoring systems.