%0 Journal Article
	%A Saman Ghaffarian and  Ilgın Gökasar
	%D 2015
	%J International Journal of Civil and Environmental Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 104, 2015
	%T Traffic Density Measurement by Automatic Detection of Vehicles Using Gradient Vectors from Aerial Images
	%U https://publications.waset.org/pdf/10001868
	%V 104
	%X This paper presents a new automatic vehicle detection
method from very high resolution aerial images to measure traffic
density. The proposed method starts by extracting road regions from
image using road vector data. Then, the road image is divided into
equal sections considering resolution of the images. Gradient vectors
of the road image are computed from edge map of the corresponding
image. Gradient vectors on the each boundary of the sections are
divided where the gradient vectors significantly change their
directions. Finally, number of vehicles in each section is carried out
by calculating the standard deviation of the gradient vectors in each
group and accepting the group as vehicle that has standard deviation
above predefined threshold value. The proposed method was tested in
four very high resolution aerial images acquired from Istanbul,
Turkey which illustrate roads and vehicles with diverse
characteristics. The results show the reliability of the proposed
method in detecting vehicles by producing 86% overall F1 accuracy
value.
	%P 973 - 977