Computer Vision Based Traffic Monitoring and Analyzing From On-Road Videos

Md. Shamim Reza Sajib; T.M. Amir-Ul-Haque Bhuiyan

Computer Vision Based Traffic Monitoring and Analyzing From On-Road Videos

Md. Shamim Reza Sajib * §

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T.M. Amir-Ul-Haque Bhuiyan

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mrinmoydas.cse

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§ Bangladesh University of Business and Technology

Computer Vision Based Traffic Monitoring and Analyzing From On-Road Videos

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Abstract

Traffic monitoring and traffic analysis is much needed to ensure a modern and convenient traffic system. However, it is a very challenging task as the traffic condition is dynamic which makes it quite impossible to maintain the traffic through traditional way. Designing a smart traffic system is also inevitable for the big and busy cities. In this paper, we propose a vision based traffic monitoring system that will help to maintain the traffic system smartly. We also generate an analysis of the traffic for a certain period, which will be helpful to design a smart and feasible traffic system for a busy city. In the proposed method, we use Haar feature based Adaboost classifier to detect vehicles from a video. We also count the number of vehicles appeared in the video utilizing two virtual detection lines (VDL). Detecting and counting vehicles by proposed method will provide an easy and cost effective solution for fruitful and operative traffic monitoring system along with information to design an efficient traffic model.

References

22 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Md. Shamim Reza Sajib, T.M. Amir-Ul-Haque Bhuiyan, mrinmoydas.cse. 2019. "Computer Vision Based Traffic Monitoring and Analyzing From On-Road Videos". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 19 (GJCST Volume 19 Issue G2).

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GJCST Volume 19 Issue G2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-G Classification I.2.8

Submission ReceivedDecember 7, 2018
Peer Review Double Blind
Handling Editor
Accepted January 5, 2019
Published January 15, 2019

Version of record

v1.2

Issue date

May 27, 2019

Language

English

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Article Matrices

Total Score: 143

Country: Bangladesh

Subject: Global Journal of Computer Science and Technology

Authors: T.M. Amir-Ul-Haque Bhuiyan, Mrinmoy Das, Md. Shamim Reza Sajib (PhD/Dr. count: 0)

View Count (all-time): 450

Total Views (Real + Logic): 2280

Total Downloads (simulated): 118

Publish Date: 2019 01, Tue

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Total Views: 2.3K

Total Downloads: 118

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