Detection System for Motorcyclist Without Helmet Using YOLO Technology

EasyChair Preprint no. 11072

Abstract

In this review paper, we are going through an already existing Automatic Detection System for Motorcyclists without Helmet and also the detection of the license plate. As we know, Two wheelers are the most useful and popular means of transport. Some reports say that one of the five bike accidents resulted in the death of the motorcyclist due to not wearing a helmet and not following the traffic rules. In this research, we propose an approach of utilizing machine learning algorithms and techniques for the detection of the helmets worn by the motorcyclist and recognition of the license plate of the motorbikes. Our methodology consists of Python-based libraries and frameworks like Tensorflow and OpenCV. For the vehicle classification, we used the Support Vector Machine (SVM) and CNN algorithms for helmet detection. For license plate recognition, Optical Character Recognition (OCR) and You Look Only Once (YOLO) algorithms are used.

Keyphrases: Helmet Detection, License plate detection, YOLO

@Booklet{EasyChair:11072,
  author = {Barkha Dange and Adarsh Uchibagle and Vedant More and Yash Kashiwaghade and Ujwal Jakhmate},
  title = {Detection System for Motorcyclist Without Helmet Using YOLO Technology},
  howpublished = {EasyChair Preprint no. 11072},

  year = {EasyChair, 2023}}