University of Engineering & Technology, Peshawar KP, Pakistan
Abstract
There is a growing demand for road traffic data of all kinds. These data are required by local and central governments for traffic surveillance, control and management. Vehicle detection and monitoring through video image processing is now considered as an attractive and flexible technique. However, the computational requirement in real-time image processing applications, such as road traffic, is beyond the capacity of conventional computers. Therefore, algorithms designed must be able to be processed in real-time. In this paper we describe a novel approach to detect and monitor vehicles in real-time. This approach is based on applying a novel morphological edge detector called SMED (Separable Morphological Edge Detector) to the key regions or windows. This method eliminates the need of a background frame, which is an essential but unreliable technique for background based image detection methods. The SMED edge detector has been applied to detect vehicles and monitor their movements at traffic junctions in real-time by using Pentium-based standard PCs
