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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
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| Paper Title: | YOLOv3 Based Real-Time Detection of Helmet and Number plate |
| Authors Name: | G. Sameeksha , Y. Yuvaraj , T. Mahidhar Varma , A. Sowmya |
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| Author Reg. ID: |
IJRTI_202348
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| Published Paper Id: | IJRTI2504171 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | ABSTRACT The project is all about creating a smart system that can check whether a person riding a motorcycle is wearing a helmet or not. The main use of the project is about the road security of the rider. At the same time, it is also used to detect the number plate of the two-wheeler. The system uses a camera and computer vision technology to check whether the rider is wearing a helmet or not. The system captures the image and reads the number plate using special software. The system uses a Convolutional Neural Network (CNN) and Optical Character Recognition (OCR). The goal of this project is to improve road safety and help traffic police to catch rule-breakers more easily without needing to check the road all the time. Through automatic recognition of helmets and number plates, the system diminishes the degree of human oversight needed, optimizing the efficacy of rule implementation and improving road safety. The system can be used on highways, traffic intersection, or installed into existing CCTV infrastructures for twenty-four-hour observation and capture if helmet infringement. Yet motor riders do not obey laws, and therefore the chance of sever injury or death in event of an accident are more. It is impossible for traffic police to visually check all the riders for helmet use easily and quickly, particularly in congested areas. Thus, an automated system is required that can check for helmet usage and detect violators effectively. |
| Keywords: | ABSTRACT The project is all about creating a smart system that can check whether a person riding a motorcycle is wearing a helmet or not. The main use of the project is about the road security of the rider. At the same time, it is also used to detect the number plate of the two-wheeler. The system uses a camera and computer vision technology to check whether the rider is wearing a helmet or not. The system captures the image and reads the number plate using special software. The system uses a Convolutional Neural Network (CNN) and Optical Character Recognition (OCR). The goal of this project is to improve road safety and help traffic police to catch rule-breakers more easily without needing to check the road all the time. Through automatic recognition of helmets and number plates, the system diminishes the degree of human oversight needed, optimizing the efficacy of rule implementation and improving road safety. The system can be used on highways, traffic intersection, or installed into existing CCTV infrastructures for twenty-four-hour observation and capture if helmet infringement. Yet motor riders do not obey laws, and therefore the chance of sever injury or death in event of an accident are more. It is impossible for traffic police to visually check all the riders for helmet use easily and quickly, particularly in congested areas. Thus, an automated system is required that can check for helmet usage and detect violators effectively. |
| Cite Article: | "YOLOv3 Based Real-Time Detection of Helmet and Number plate ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b578-b583, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504171.pdf |
| Downloads: | 000362 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2504171
Registration ID:202348
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: b578-b583 Country: Hyderabad, Telangana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504171 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504171 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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