A parallel pipeline based multiprocessor system for real-time measurement of road traffic parameters

被引:10
|
作者
Siyal, MY
Fathi, M
Atiquzzaman, M [1 ]
机构
[1] Univ Dayton, Dept Elect & Comp Engn, Dayton, OH 45469 USA
[2] Nanyang Technol Univ, Sch EEE, Singapore 639798, Singapore
关键词
D O I
10.1006/rtim.1999.0190
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Real-time measurement and analysis of road traffic flow parameters such as volume, speed and queue are increasingly required for traffic control and management. Image processing is considered as an attractive and flexible technique for automatic analysis of road traffic scenes for the measurement and data collection of road traffic parameters. In this paper, the authors describe a novel image processing based approach for analysis of road traffic scenes. Combined background differencing and edge detection techniques are used to detect vehicles and measure various traffic parameters such as vehicle count and the queue length, A RISC based multiprocessor system was designed to enable real-time execution of the authors algorithm, The multiprocessor system has nine processing modules connected in a parallel pipeline fashion. Results shows that the authors multiprocessor system is able to provide measurement of traffic parameters in real-time, Results are presented for real tests of our system by analysing traffic scenes on the highways of Singapore. (C) 2000 Academic Press.
引用
收藏
页码:241 / 249
页数:9
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