%0 Journal Article
	%A Saad M. Al-Garni and  Adel A. Abdennour
	%D 2008
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 20, 2008
	%T Intelligent Video-Based Monitoring of Freeway Traffic
	%U https://publications.waset.org/pdf/490
	%V 20
	%X Freeways are originally designed to provide high
mobility to road users. However, the increase in population and
vehicle numbers has led to increasing congestions around the world.
Daily recurrent congestion substantially reduces the freeway capacity
when it is most needed. Building new highways and expanding the
existing ones is an expensive solution and impractical in many
situations. Intelligent and vision-based techniques can, however, be
efficient tools in monitoring highways and increasing the capacity of
the existing infrastructures. The crucial step for highway monitoring
is vehicle detection. In this paper, we propose one of such
techniques. The approach is based on artificial neural networks
(ANN) for vehicles detection and counting. The detection process
uses the freeway video images and starts by automatically extracting
the image background from the successive video frames. Once the
background is identified, subsequent frames are used to detect
moving objects through image subtraction. The result is segmented
using Sobel operator for edge detection. The ANN is, then, used in
the detection and counting phase. Applying this technique to the
busiest freeway in Riyadh (King Fahd Road) achieved higher than
98% detection accuracy despite the light intensity changes, the
occlusion situations, and shadows.
	%P 1660 - 1666