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Helmet and Number Plate Detection
Subject area: Science,Engineering and Technology · Area of research: Deep Learning, AIML, Image and Video Processing
Abstract
This report presents a real-time object detection system for identifying motorcyclists without helmets and detecting vehicle number plates using the YOLO (You Only Look Once) algorithm. The primary objective is to enhance road safety and aid law enforcement by automating the surveillance process. The model is trained using a dataset consisting of annotated images of motorcyclists with and without helmets, as well as vehicles with visible number plates. YOLO?s fast and accurate detection capabilities enable efficient identification of both safety violations and vehicle registration details. The system successfully detects and classifies helmet usage and localizes number plates in real-time, making it suitable for deployment in smart traffic monitoring systems. The results demonstrate high precision and recall, confirming YOLO?s effectiveness in multi-object detection tasks within the traffic surveillance domain.
How to cite this paper
@article{1708702,
author = {Pawan Kumar Singh, Syed Md Sheeraz , Udit Singh, Madhup Agrawal},
title = {Helmet and Number Plate Detection},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {11},
pages = {2085-2108},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708702.pdf},
abstract = {This report presents a real-time object detection system for identifying motorcyclists without helmets and detecting vehicle number plates using the YOLO (You Only Look Once) algorithm. The primary objective is to enhance road safety and aid law enforcement by automating the surveillance process. The model is trained using a dataset consisting of annotated images of motorcyclists with and without helmets, as well as vehicles with visible number plates. YOLO?s fast and accurate detection capabilities enable efficient identification of both safety violations and vehicle registration details. The system successfully detects and classifies helmet usage and localizes number plates in real-time, making it suitable for deployment in smart traffic monitoring systems. The results demonstrate high precision and recall, confirming YOLO?s effectiveness in multi-object detection tasks within the traffic surveillance domain.},
month = {May},
}