An Automatic Traffic Rules Violation Detection and Number Plate Recognition System for Bangladesh

AIUB Journal of Science and Engineering

View Publication Info
 
 
Field Value
 
Title An Automatic Traffic Rules Violation Detection and Number Plate Recognition System for Bangladesh
 
Creator Shahrear, Raian
Rahman, Md. Anisur
Islam, Atif
Dey, Chamak
Zishan, Md. Saniat Rahman
 
Subject YOLOv3
Darknet
OpenCV
Object detection
Traffic Rule
violation detection
ANPR
 
Description The traffic controlling system in Bangladesh has not been updated enough with respect to fast improving technology. As a result, traffic rules violation detection and identification of the vehicle has become more difficult as the number of vehicles is increasing day by day. Moreover, controlling traffic is still manual. To solve this problem, the traffic controlling system can be digitalized by a system that consists of two major parts which are traffic rules violation detection and number plate recognition. In this research, these processes are done automatically which is based on machine learning, deep learning, and computer vision technology. Before starting this process, an object on the road is identified through the YOLOv3 algorithm. By using the OpenCV algorithm, traffic rules violation is detected and the vehicle that violated these rules is identified. To recognize the number plate of the vehicle, image acquisition, edge detection, segmentation of characters is done sequentially by using Convolution Neural Network (CNN) in MATLAB background. Among the traffic rules, the following traffic signal is implemented in this research.
 
Publisher American International University-Bangladesh
 
Date 2020-09-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ajse.aiub.edu/index.php/ajse/article/view/97
 
Source AIUB Journal of Science and Engineering (AJSE); Vol 19 No 2 (2020): AJSE Volume:19 Issue:2 (2020); 87 - 98
2520-4890
1608-3679
 
Language eng
 
Relation http://ajse.aiub.edu/index.php/ajse/article/view/97/72
 
Rights Copyright (c) 2020 AIUB Journal of Science and Engineering (AJSE)
https://creativecommons.org/licenses/by-nc-nd/4.0
 

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