{"title":"Advancements in Safety: Utilizing CNNs for Helmet Detection and License Plate Recognition","authors":"S. Krishnaveni","doi":"10.22214/ijraset.2024.63519","DOIUrl":null,"url":null,"abstract":"Abstract: In contemporary times, road accidents stand out as significant contributors to human fatalities. Among these, motorcycle accidents are prevalent and often result in severe injuries. Helmets serve as crucial protective gear for motorcyclists, yet adherence to helmet laws remains lacking. To overcome this issue, a system that uses image processing and convolutional neural networks (CNNs) has been created. This system encompasses motorbike detection, helmet classification (helmet vs. no helmet), and motorbike license plate recognition. Motorbikes are initially identified using YOLOV3. Afterward, a CNN evaluates if the biker is wearing a helmet. In cases where a helmet violation is detected, the system utilizes tesseract OCR to recognize the motorcycle's license plate, facilitating enforcement measures.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"15 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Research in Applied Science and Engineering Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22214/ijraset.2024.63519","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
Abstract: In contemporary times, road accidents stand out as significant contributors to human fatalities. Among these, motorcycle accidents are prevalent and often result in severe injuries. Helmets serve as crucial protective gear for motorcyclists, yet adherence to helmet laws remains lacking. To overcome this issue, a system that uses image processing and convolutional neural networks (CNNs) has been created. This system encompasses motorbike detection, helmet classification (helmet vs. no helmet), and motorbike license plate recognition. Motorbikes are initially identified using YOLOV3. Afterward, a CNN evaluates if the biker is wearing a helmet. In cases where a helmet violation is detected, the system utilizes tesseract OCR to recognize the motorcycle's license plate, facilitating enforcement measures.