Implementation of traffic flow measuring algorithm using real-time dynamic image processing

Authors:
Tae-Seung Lee;Eung-Min Lee;Hyeong-Taek Park;Young-Kil Kwag;Sang-Seok Lim;Joong-Hwan Baek;Byong-Won Hwang
Affiliations:
Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea;Hankuk Aviation University, School of Electronics, Telecommunication and Computer Engineering, Koyang-city, Kyonggi-do, Seoul, The Republic of Korea
Venue:
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Year:
2003

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Abstract

In this paper, an automatic traffic flow measuring system and a real-time image processing algorithm have been developed. The picture of moving vehicles taken by an industrial television (ITV) camera are digitized into sample points in odd ITV frames and the points are processed in even ITV frames by a personal computer. We detect the presence of vehicles by comparing the brightness of the sample points of vehicle with that of the road. After eliminating noises contained in the digitized sample points by appropriate smoothing techniques, we obtain a contour of each vehicle. Using the contour, the number of passing vehicles is effectively measured by counting the number of sample points of each vehicle. Also the type of a vehicle is easily figured out by counting the number of sample points corresponding to the width of vehicle's contour. The performance of the proposed algorithm is demonstrated by actual implementation. From the experimental results 1-2% measurement error was observed.