Traffic Congestion Estimation using Video without Vehicle Tracking

被引：0

作者：

Siswoyo, Antony A. ^{[1
]}

Joelianto, Endra ^{[1
]}

Sutarto, Herman Y. ^{[2
]}

机构：

[1] Inst Teknol Bandung, Fac Ind Technol, Instrumentat & Control Master Program, Bandung 40132, Indonesia

[2] PT Pusat Riset Energi, Dept Intelligent Syst, Bandung 40226, Indonesia

来源：

INTERNETWORKING INDONESIA | 2022年 / 14卷 / 01期

关键词：

Traffic control; Traffic sensor; Image thresholding; Expectation maximization; Congestion estimation; Vehicle tracking;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this study, a traffic density monitoring system using the expectation maximization (EM) algorithm was tested on video data with varying traffic density levels. Experiments were conducted to find the most accurate image thresholding method to preprocess the images before they are fed to the EM algorithm. The algorithm successfully detected traffic density, separating it into two categories, namely 'congested' and 'smooth'. Using the Bradley-Roth method for image thresholding produced the most accurate results.

引用

页码：33 / 37

页数：5

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