Computer Vision Based Approach for Overspeeding Problem in Smart Traffic System

G. Singh, Anurag Gupta, B. Gupta, Sanchita Ghosh
{"title":"Computer Vision Based Approach for Overspeeding Problem in Smart Traffic System","authors":"G. Singh, Anurag Gupta, B. Gupta, Sanchita Ghosh","doi":"10.1109/ITEC-India53713.2021.9932508","DOIUrl":null,"url":null,"abstract":"With the growth in the urban population, count of vehicles on the road is also increasing drastically, traffic control in cities has become one of the most pressing challenges for the transportation system. A variety of different systems have been implemented across the country and around the world to resolve this issue. But most of them have proved inefficient to be implemented on a large scale that too in a developing country like India. Traffic management and related creative technologies are needed in the era of Machine Learning, Internet of Things (IoT), Image and Video processing, and Computer Vision in order to create more viable future cities. This paper presents a computer vision based approach for overspeed vehicle detection in Smart Traffic System (STS). Proposed overspeed vehicle detection system is based on centroid tracking and mark gap distance concept followed by OpenCV and Tesseract based method for license plate recognition. Primary purpose of the proposed system is to decrease cases of overspeeding and high death rates because of accidents. The accuracy of the proposed system is approximately 80% in detection of the overspeed vehicles.","PeriodicalId":162261,"journal":{"name":"2021 IEEE Transportation Electrification Conference (ITEC-India)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Transportation Electrification Conference (ITEC-India)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITEC-India53713.2021.9932508","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 growth in the urban population, count of vehicles on the road is also increasing drastically, traffic control in cities has become one of the most pressing challenges for the transportation system. A variety of different systems have been implemented across the country and around the world to resolve this issue. But most of them have proved inefficient to be implemented on a large scale that too in a developing country like India. Traffic management and related creative technologies are needed in the era of Machine Learning, Internet of Things (IoT), Image and Video processing, and Computer Vision in order to create more viable future cities. This paper presents a computer vision based approach for overspeed vehicle detection in Smart Traffic System (STS). Proposed overspeed vehicle detection system is based on centroid tracking and mark gap distance concept followed by OpenCV and Tesseract based method for license plate recognition. Primary purpose of the proposed system is to decrease cases of overspeeding and high death rates because of accidents. The accuracy of the proposed system is approximately 80% in detection of the overspeed vehicles.
基于计算机视觉的智能交通系统超速问题研究
随着城市人口的增长,道路上的车辆数量也在急剧增加,城市交通控制已成为交通系统面临的最紧迫挑战之一。为了解决这个问题,全国和世界各地都实施了各种不同的制度。但事实证明,在印度这样的发展中国家大规模实施这些措施效率低下。在机器学习、物联网(IoT)、图像和视频处理、计算机视觉时代,为了创造更可行的未来城市,需要交通管理和相关的创新技术。提出了一种基于计算机视觉的智能交通系统超速车辆检测方法。提出了基于质心跟踪和标记间隙距离概念的超速车辆检测系统,并采用基于OpenCV和Tesseract的车牌识别方法。拟议的系统的主要目的是减少超速和高死亡率,因为事故。该系统对超速车辆的检测准确率约为80%。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信