Real-time vehicle tracking for traffic monitoring systems

被引：0

作者：

Hu S. ^{[1
]}

Zhang X. ^{[1
]}

Wu N. ^{[2
]}

机构：

[1] Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao

[2] Key Laboratory of Measurement Technology & Instrumentation of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao

来源：

High Technology Letters | 2016年 / 22卷 / 03期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Covariance matching; Genetic algorithms; Traffic monitoring system; Vehicle tracking;

D O I：

10.3772/j.issn.1006-6748.2016.03.003

中图分类号：

学科分类号：

摘要：

A real-time vehicle tracking method is proposed for traffic monitoring system at road intersections, and the vehicle tracking module consists of an initialization stage and a tracking stage. License plate location based on edge density and color analysis is used to detect the license plate region for tracking initialization. In the tracking stage, covariance matching is employed to track the license plate. Genetic algorithm is used to reduce the computational cost. Real-time image tracking of multi-lane vehicles is achieved. In the experiment, test videos are recorded in advance by recorders of actual E-police systems at several different city intersections. In the tracking module, the average false detection rate and missed plates rate are 1.19%, and 1.72%, respectively. Copyright © by HIGH TECHNOLOGY LETTERS PRESS.

引用

页码：248 / 255

页数：7

共 27 条

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