NDLI: A simple method for calculating vehicle density in traffic images

Content Provider	IEEE Xplore Digital Library
Author	Royani, T. Haddadnia, J. Pooshideh, M.
Copyright Year	2010
Description	Author affiliation: Electrical Engineering faculty, Tarbiat Moallem University of Sabzevar, Iran (Royani, T.; Haddadnia, J.; Pooshideh, M.)
Abstract	Calculating of vehicles density in traffic images is a challenging research topic as it has to directly deal with hostile but realistic conditions on the road, such as uncontrolled illuminations, cast shadows, and visual occlusion. Yet, the outcome of being able to accurately count and resolve vehicles under such conditions has tremendous benefit to traffic surveillance. Accurate vehicle count enables the extraction of important traffic information such as congestion level and lane occupancy. There are different methods for vehicles counting from traffic images that emphasize on the accuracy, but most of them suffer from long time process and computational complexity, so they can't be used in real-time condition. This paper proposed a novel simple method for traffic density calculation in multiple vehicle occlusions based on counting object pixels and assigning a distance index to each region of image that concentrates on time and computational complexity and has tolerable accuracy in traffic density calculation. Suppose that the occluded vehicles are segmented from the road background by previously proposed vehicle segmentation method. The proposed method has been tested on real-world monocular traffic images with multiple vehicle occlusions. The experimental results show that the proposed method can provide real-time and useful information for traffic surveillance.
Starting Page	1
Ending Page	4
File Size	310282
Page Count	4
File Format	PDF
ISBN	9781424497065
e-ISBN	9781424497089
DOI	10.1109/IranianMVIP.2010.5941176
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-27
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Accuracy Estimation Traffic control Traffic surveillance Vehicle density Cameras Computational complexity Pixel Vehicles
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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