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Machine vison-based system for vehicle classification and counting using YOLO

This paper proposes a machine vision-based system that is used for vehicle classification and counting. Vehicle classifier and counter are a very crucial in road design to determine the road load capacity. It is also important to monitor, manage, and analyze the traffic flow. In this work, the input...

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Main Authors: Refaie, Elbaraa, Mohd. Faudzi, Ahmad Athif
Format: Conference or Workshop Item
Published: 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/98601/
http://dx.doi.org/10.1007/978-981-16-8484-5_37
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id my.utm.98601
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spelling my.utm.986012023-01-21T01:18:39Z http://eprints.utm.my/id/eprint/98601/ Machine vison-based system for vehicle classification and counting using YOLO Refaie, Elbaraa Mohd. Faudzi, Ahmad Athif TK Electrical engineering. Electronics Nuclear engineering This paper proposes a machine vision-based system that is used for vehicle classification and counting. Vehicle classifier and counter are a very crucial in road design to determine the road load capacity. It is also important to monitor, manage, and analyze the traffic flow. In this work, the input video is obtained from a static video camera and from drone-captured video to count the cars, determine its direction and to classify the vehicle types on the road. The data will be fed to the vision-based system that will pass the frames captured by the camera through a YOLO neural network to classify the vehicles. Then, the cars contours are used to determine the car path that determines in which direction the vehicle is moving before it is being counted. The system will display the total number of vehicles moved in each direction and while identifying each vehicle’s type. This work is possible to be used for other application such as surveillance tracking and monitoring. 2022 Conference or Workshop Item PeerReviewed Refaie, Elbaraa and Mohd. Faudzi, Ahmad Athif (2022) Machine vison-based system for vehicle classification and counting using YOLO. In: International Conference on Computational Intelligence in Machine Learning, ICCIML 2021, 1 - 2 June 2021, Virtual, Online. http://dx.doi.org/10.1007/978-981-16-8484-5_37
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Refaie, Elbaraa
Mohd. Faudzi, Ahmad Athif
Machine vison-based system for vehicle classification and counting using YOLO
description This paper proposes a machine vision-based system that is used for vehicle classification and counting. Vehicle classifier and counter are a very crucial in road design to determine the road load capacity. It is also important to monitor, manage, and analyze the traffic flow. In this work, the input video is obtained from a static video camera and from drone-captured video to count the cars, determine its direction and to classify the vehicle types on the road. The data will be fed to the vision-based system that will pass the frames captured by the camera through a YOLO neural network to classify the vehicles. Then, the cars contours are used to determine the car path that determines in which direction the vehicle is moving before it is being counted. The system will display the total number of vehicles moved in each direction and while identifying each vehicle’s type. This work is possible to be used for other application such as surveillance tracking and monitoring.
format Conference or Workshop Item
author Refaie, Elbaraa
Mohd. Faudzi, Ahmad Athif
author_facet Refaie, Elbaraa
Mohd. Faudzi, Ahmad Athif
author_sort Refaie, Elbaraa
title Machine vison-based system for vehicle classification and counting using YOLO
title_short Machine vison-based system for vehicle classification and counting using YOLO
title_full Machine vison-based system for vehicle classification and counting using YOLO
title_fullStr Machine vison-based system for vehicle classification and counting using YOLO
title_full_unstemmed Machine vison-based system for vehicle classification and counting using YOLO
title_sort machine vison-based system for vehicle classification and counting using yolo
publishDate 2022
url http://eprints.utm.my/id/eprint/98601/
http://dx.doi.org/10.1007/978-981-16-8484-5_37
_version_ 1755872331739168768
score 13.211869

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