NDLI: Traffic monitoring based on real-time image tracking

Content Provider	IEEE Xplore Digital Library
Author	Ching-Po Lin Jen-Chao Tai Kai-Tai Song
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan (Ching-Po Lin; Jen-Chao Tai; Kai-Tai Song)
Abstract	This paper presents a study on a stand-alone image tracking system for automatic traffic monitoring. The proposed image tracker consists of three parts: an edge detection module, an image tracking module and a traffic monitoring module. The edge-detection module is a special designed circuit board, which features fast CCD image processing and feature extraction. Frame rate (60 Hz) edge detection of an image with resolution of 320/spl times/240 pixels is obtained on-board. The image tracking module performs the vehicle tracking in real time. Adopting active contour models and Kalman filtering techniques, we successfully achieved real-time image tracking of multi-lane moving vehicles. The traffic-monitoring module determines the traffic information from the tracked locations of vehicles. The current system provides three types of traffic information: the velocity of multi-lane vehicles, the number of vehicles and car accident detection. Experimental results are presented to demonstrate the real-time tracking of vehicles on an urban artery.
Sponsorship	IEEE Robotics & Autom. Soc. Nat. Sci. Council, Taiwan, Ministr. Educ., Taiwan
Starting Page	2091
Ending Page	2096
File Size	420115
Page Count	6
File Format	PDF
ISBN	0780377362
ISSN	10504729
DOI	10.1109/ROBOT.2003.1241902
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-14
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Image edge detection Traffic control Computerized monitoring Printed circuits Charge coupled devices Image processing Feature extraction Image resolution Pixel
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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