Vision Based Vehicle Detection and Traffic Parameter Extraction

Mei YU  Yong-Deak KIM  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.6   pp.1461-1470
Publication Date: 2001/06/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Papers Selected from 2000 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2000))
vehicle detection,  shadow rejection,  traffic parameter extraction,  traffic monitoring,  

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Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.