Methods of vehicle recognition and detecting traffic rules violations on motion picture based on opencv framework

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dc.citation.epage111
dc.citation.issueVolume 6, № 2
dc.citation.journalTitleAdvances in Cyber-Physical Systems
dc.citation.spage105
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorFastiuk, Yevhen
dc.contributor.authorBachynskyy, Ruslan
dc.contributor.authorHuzynets, Nataliia
dc.date.accessioned2022-12-01T09:13:06Z
dc.date.available2022-12-01T09:13:06Z
dc.date.issued2021
dc.date.submitted2022
dc.description.abstractIn this era, people using vehicles is getting increased day by day. As pedestrians leading a dog for a walk, or hurrying to their workplace in the morning, we’ve all experienced unsafe, fast-moving vehicles operated by inattentive drivers that nearly mow us down. Many of us live in apartment complexes or housing neighborhoods where ignorant drivers disregard safety and zoom by, going way too fast. To plan, monitor and also control these vehicles is becoming a big challenge. In the article, we have come up with a solution to the above problem using the video surveillance considering the video data from the traffic cameras. Using computer vision and deep learning technology we will be able to recognize violations of rules. This article will describe modern CV and DL methods to recognize vehicle on the road and traffic violations of rules by them. Implementation of methods can be done using OpenCV Python as a tool. Our proposed solution can recognize vehicles, track their speed and help in counting the objects precisely.
dc.format.pages105-111
dc.identifier.citationFastiuk Ye. Methods of vehicle recognition and detecting traffic rules violations on motion picture based on opencv framework / Yevhen Fastiuk, Ruslan Bachynskyy, Nataliia Huzynets // Advances in Cyber-Physical Systems. – Lviv : Lviv Politechnic Publishing House, 2021. – Volume 6, № 2. – P. 105–111 . – Bibliography: 10 titles.
dc.identifier.doihttps://doi.org/10.23939/acps2021.02.105
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/57240
dc.language.isoen
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofAdvances in Cyber-Physical Systems
dc.relation.references[1] Bachynskyy, R., Chaku, O., and Huzynets, N. (2017) A Software Service for the Garbage Type Recognition Based on the Mobile Computing Devices With Graphical Data Input. Advances in Cyber-Physical Systems, 5(1), pp. 1–7. DOI: 10.23939/acps2020.01.001. [2] Sowmya, K.M., Rekha, B., Praveen, S.K. (2021) Real Time Moving Vehicle Congestion Detection and Tracking using OpenCV. Turkish Journal of Computer and Mathematics Education, 12(10), pp. 273–279. Available at: https://www.turcomat.org/index.php/turkbilmat/article/view/ 4139. [Accessed 22 November 2021]. [3] OpenCV (2021) Home – OpenCV. [online] Available at: http://opencv.org/ [Accessed 22 November 2021]. [4] Kushnir, D., Paramud, Y. (2019) Methods for real-time object searching and recognizing in video images on ios mobile platform. Computer systems and network, 1(1), pp. 24–34, DOI: 10.23939/csn2019.01.024. [5] TechVidvan (2021) Vehicle Counting, Classification & Detection using OpenCV & Python. [online] Available at: https://techvidvan.com/tutorials/opencv-vehicle-detection classification-counting/ [Accessed 21 November 2021]. [6] Redmon, J., Divvala, S., Girshick, R., Farhadi, A. (2016) You Only Look Once: Unified, Real-Time Object Detection. CoRR, abs/1506.02640. Available at: http://arxiv. org/abs/1506.02640. [Accessed22 November 2021]. [7] Medium (2021) YOLO v1: Part 1. [online] Available at: https://medium.com/adventures-with-deep-learning/yolo-v1- part-1-cfb47135f81f/ [Accessed 22 November 2021]. [8] Puyda, V., Stoian, A. (2020) On Methods of Object Detection in Video Streams. Computer Systems and Networks, 2(1), pp. 80–87, DOI: 10.23939/csn2020.01.080. [9] Wiki (2021) Euclidean distance. [online] Available at: https://en.wikipedia.org/wiki/Euclidean_distance/ [Accessed 22 November 2021]. [10] Pyimagesearch (2021) OpenCV Vehicle Detection, Tracking, and Speed Estimation. [online] Available at: https://www. pyimagesearch.com/2019/12/02/opencv vehicle-detection-tracking-and-speed-estimation/ [Accessed 21 November 2021].
dc.subjectOpenCV, Object Detection, Object Tracking, Deep Neural Network, CV
dc.titleMethods of vehicle recognition and detecting traffic rules violations on motion picture based on opencv framework
dc.typeArticle

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Advances In Cyber-Physical Systems. – 2021. – Vol. 6, No. 2