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Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Open Access Research Article

Deep learning based highway vehicles detection and counting system using computer vision

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pp. 997–1008Vol. 44Issue 5July 2023DOI: 10.47974/JIOS-1462XML
Received:
08 Feb 2023
Published Online:
10 Oct 2023
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1462
Pages:
997–1008

Abstract

In the field of highway management, intelligent vehicle detection and counting are becoming increasingly significant. City planners have been fighting the issue of traffic analysis for years. To analyze traffic and streamline the process, intelligent methods are being created. The type of vehicles and the number of vehicles in an area over some arbitrary time period may be taken into account. Over the years, humans have created a variety of mechanisms, because the vehicles are come in different sizes, it is still difficult to identify them, which can directly impact the accuracy of vehicles count. In the field of vision research, computer vision is one of the most often used applications for traffic scenarios. A variety of computer vision applications, including object detection and categorization, have proven that deep learning techniques like Convolutional Neural Networks (CNNs) greatly outperform conventional approaches. Hence in this work, deep learning-based highway vehicles detection and count system suing computer vision is presented. Vehicles on the highway can be efficiently detected by this technique. YOLOv3 (You Look Only Once Version 3) is a real-time object detection technique which is used to detect vehicles in real-time. Precision, recall and real-time rate are measured to evaluate the performance of this system.

Keywords

Subject Classifications

Primary 68T07Secondary 68M25

References

[1] Janak D. Trivedi, Sarada Devi Mandalapu, Dhara H. Dave, “Vision-based real-time vehicle detection and vehicle speed measurement using morphology and binary logical operation”, Journal of Industrial Information Integration, Volume 27 (May 2022), 100280,doi.org/10.1016/j.jii.2021.100280.
[2] Mohana, Rahul Kejriwal, Ritika H J, Arpit Arora, “Artificial Intelligence (AI) Enabled Vehicle Detection and counting Using Deep Learning”, 2022 International Conference on Computer Communication and Informatics (ICCCI-2022), DOI: 10.1109/ICCCI54379.2022.9740929.
[3] Apeksha P Kulkarni, Vishwanath P Baligar, “Real Time Vehicle Detection, Tracking and Counting Using Raspberry-Pi”, Proceedings of the Second International Conference on Innovative Mechanisms for Industry Applications (ICIMIA 2020), 978-1-7281-4167-1.
[4] Genyuan Cheng, Yubin Guo, Xiachum Cheng, Dongligang Wang, Jiandong Zhao, “Real-time detection of vehicle speed based on Video image”, 2020 12th International Conference on measuring Technology and Mechatronics Automation (ICMTMA), 2157-1481/20, 2020 IEEE.
[5] Xiangdi Liu, Yunlong Dong, Zelin Deng, “Deep Highway Multi-Camera Vehicle Re-ID with Tracking Context”, 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC 2020), 978-1-7281-4390-3/20.
[6] Zillur Rahman, Amit Mazumder Ami, Muhammad Ahsan Ullah, “A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking”, 2020 IEEE Region 10 Symposium (TENSYMP), 5-7 June 2020, Dhaka, Bangladesh, 978-1-7281-7366-5/20.
[7] P. Nagaraj Raj Varshith Reddy Mohammed Sabeehuddin, SriChandana Reddy, V Santhosh, “A Video based Vehicle Detection, Counting and Classification System”, Alochana Chakra Journal, ISSN NO:2231-3990,Volume IX, Issue V, May/2020.
[8] Mohammed HazimAlkawaz, Maran Tamil Veeran, Omar Ismael Al-Sanjary, “Vehicle Tracking and Reporting System using Robust Algorithm”, 2019 IEEE 7th Conference on Systems, Process and Control (ICSPC 2019), 13–14 December 2019, Melaka, Malaysia, 978-1-7281-1826-0/19.
[9] AryuantoSoetedjo, I KomangSomawirata, “Improving On-Road Vehicle Detection Performance by Combining Detection and Tracking Techniques”, 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems, 978-1-5386-7226-6/18, DOI: 10.1109/ACIRS.2018.8467217.
[10] Boris A. Alpatov, Pavel V. Babayan, Maksim D. Ershov, “Vehicle Detection and Counting System for Real-Time Traffic Surveillance”, 7thMediterranean Conference on Embedded Computing MECO’2018, Budva, Montenegro.
[11] Xiao-Feng Gu, Zi-Wei Chen, Ting-Song Ma, Fan Li, Long Yan, “Real-Time Vehicle Detection and Tracking using Deep Neural Networks”, 2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 978-1-5090-6126-6/16, 2016 IEEE,DOI: 10.1109/ICCWAMTIP.2016.8079830.
[12] Huang Guan, Wang Xingang, Wu Wenqi, Zhou Han, Wu Yuanyuan, “Real-Time Lane-Vehicle Detection and Tracking System”,Chinese Control and Decision Conference (CCDC) (2016).
[13]  Kumar, A. et. al.,” Improving the visual quality of a size deterministic visual cryptography scheme for Grayscale Images”, Journal of Discrete Mathematical Sciences and Cryptography 25:4, pages 1113-1123 (2022). 
[14] Sharma, H. et. al.    “Commutative encryption-based video encoding technique with high-efficiency & video adaptation capabilities”, Journal of Discrete Mathematical Sciences and Cryptography, 24:8, 2207-2219 (2021), DOI: https://doi.org/10.1080/09720529.2021. 2011099. 
[15] Pasupathy, Vijayalakshmi, and RashmitaKhilar “Advancements in deep structured learning based medical image interpretation” Journal of Information and Optimization Sciences 43.5 : 1131-1138 (2022). 
[16] Abdulghani, Farah A., and Nada AZ Abdullah. “Hybrid deep learning model for Arabic text classification based on mutual information”, Journal of Information and Optimization Sciences  43.8 : 1901-1908 (2022).

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