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Journal of Information Science and Engineering, Vol. 24 No. 2, pp. 411-423 (March 2008)

Real-Time Background Estimation of Traffic Imagery Using Group-Based Histogram*

Kai-Tai Song and Jen-Chao Tai+
Department of Electrical and Control Engineering
National Chiao Tung University
Hsinchu, 300 Taiwan
+Department of Mechanical Engineering
Minghsin University of Science and Technology
Shinfen, 304 Taiwan

This paper presents a novel background estimation method for a vision-based traffic monitoring system using a single Gaussian scheme. An algorithm of group-based histogram (GBH) is proposed to build the background Gaussian model of each pixel from traffic image sequences. This algorithm features improved robustness against transient stop of foreground objects and sensing noise. Furthermore, the method features low computational load, thus meets the real-time requirements in many practical applications. The proposed method has been applied to a vision-based traffic parameter estimation system to segment moving vehicles from image sequences. Given degraded compressive traffic images from on-line internet cameras, the image processing system successfully detect various vehicles in the traffic imagery. Practical experimental results demonstrate that traffic flow can be measured in real time with satisfactory accuracy.

Keywords: background segmentation, image processing, group-based histogram, traffic parameters, traffic monitoring

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Received January 4, 2005; revised May 1, 2006; accepted November 1, 2006.
Communicated by Jenq-Neng Hwang.
* This work was partly supported by the National Science Council of Taiwan, R.O.C., under grant No. NSC 92-2213-E009-013 and by the Ministry of Education, under the program of Promoting University Academic Excellence grant EX-91-E-FA06-4-4.