Over-Speed and License Plate Detection of Vehicles

S. Dhonde, Jayesh Mirani, Sunit Patwardhan, K. Bhurchandi
{"title":"Over-Speed and License Plate Detection of Vehicles","authors":"S. Dhonde, Jayesh Mirani, Sunit Patwardhan, K. Bhurchandi","doi":"10.1109/PCEMS55161.2022.9808085","DOIUrl":null,"url":null,"abstract":"With the swift expansion of the global economy, cities in various nations may face day to day problems like road congestion, frequent accidents, deterioration of the traffic conditions, or other urban traffic concerns. Vehicle detection technology based on video can collect a wealth of information from video frame sequences, such as vehicle speed, vehicle type, and vehicle number plate, at a cheap cost and with great efficiency. These electronic technologies are not only useful in people’s daily lives, but they also provide management with safe and efficient services. If we solely rely on human resources, such as law enforcement officers, we may face numerous issues, including high costs and low efficiency. We have built an integrated system for speed and license plate detection of vehicles. In the method presented here, the vehicle is first segmented and extracted from a video feed, using YOLOv5 algorithm. Next, the speed of the car is calculated using a simple algorithm and then the license plate snapshots are detected. Finally, optical character recognition is applied on the license plate image. This paper presents a thorough analysis of the cutting-edge approaches for detecting and recognising vehicles, their speeds and number plates.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCEMS55161.2022.9808085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the swift expansion of the global economy, cities in various nations may face day to day problems like road congestion, frequent accidents, deterioration of the traffic conditions, or other urban traffic concerns. Vehicle detection technology based on video can collect a wealth of information from video frame sequences, such as vehicle speed, vehicle type, and vehicle number plate, at a cheap cost and with great efficiency. These electronic technologies are not only useful in people’s daily lives, but they also provide management with safe and efficient services. If we solely rely on human resources, such as law enforcement officers, we may face numerous issues, including high costs and low efficiency. We have built an integrated system for speed and license plate detection of vehicles. In the method presented here, the vehicle is first segmented and extracted from a video feed, using YOLOv5 algorithm. Next, the speed of the car is calculated using a simple algorithm and then the license plate snapshots are detected. Finally, optical character recognition is applied on the license plate image. This paper presents a thorough analysis of the cutting-edge approaches for detecting and recognising vehicles, their speeds and number plates.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
车辆超速和车牌检测
随着全球经济的迅速发展,各个国家的城市可能面临着诸如道路拥堵、事故频发、交通状况恶化或其他城市交通问题等日常问题。基于视频的车辆检测技术可以从视频帧序列中采集到丰富的车辆速度、车型、车牌号等信息,成本低,效率高。这些电子技术不仅在人们的日常生活中有用,而且还为管理提供了安全高效的服务。如果我们仅仅依靠人力资源,比如执法人员,我们可能会面临很多问题,包括成本高,效率低。我们建立了一个综合的车辆速度和车牌检测系统。在这里提出的方法中,首先使用YOLOv5算法从视频馈送中分割和提取车辆。接下来,使用简单的算法计算汽车的速度,然后检测车牌快照。最后,对车牌图像进行了光学字符识别。本文提出了检测和识别车辆,他们的速度和车牌的尖端方法的透彻分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Real-time Track and Anomaly Detection in Complex Railway Environment Physical Layer Security Analysis in Ambient Backscatter Communication With Source and Reader Mobility Relay Selection in SWIPT-enabled Cooperative Networks Fractal Analysis of Radon Coefficients for No-Reference Video Quality Assessment (NR-VQA) PCEMS 2022 Cover Page
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1