Real-Time Helmet Detection and Number Plate Extraction Using Computer Vision

Authors

  • Jyoti Prakash-Borah National Institute of Technology
  • Prakash Devnani National Institute of Technology
  • Sumon Kumar-Das National Institute of Technology
  • Advaitha Vetagiri National Institute of Technology
  • Partha Pakray National Institute of Technology

DOI:

https://doi.org/10.13053/cys-28-1-4906

Keywords:

Image dataset, YOLOv8, deep learning model, object detection, image processing algorithms

Abstract

In the contemporary landscape, two-wheelershave emerged as the predominant mode oftransportation, despite their inherent risk due to limitedprotection. Disturbing data from 2020 reveals a dailytoll of 304 lives lost in India in road accidents involvingtwo-wheeler riders without helmets, emphasizing theurgent need for safety measures. Recognizing thecrucial role of helmets in mitigating risks, governmentshave made riding without one a punishable offense,employing manual strategies for enforcement withlimitations in speed and weather conditions. In today’sworld of advancing technology, we can leveragethe power of computer vision and deep learning totackle this problem. This can eliminate the need forconstant human surveillance to be kept on riders andcan automate this process, thus enforcing law andorder as well as making this process efficient. Ourproposed solution utilizes video surveillance and theYOLOv8 deep learning model for automatic helmetdetection. The system employs pure machine learningto identify helmet types with minimal computation costby utilizing various image processing algorithms. Oncethe helmet-less person is detected, the number platecorresponding to the rider’s motorcycle is also detectedand extracted using computer vision techniques. Thisnumber plate is then stored in a database thus allowingfurther intervention to be done in this matter by theauthorities to ensure penalties and enforce safety rulesproperly. The model developed achieves an overallaccuracy score of 93.6% on the testing data, thusshowcasing good results on diverse datasets.

Downloads

Published

2024-03-20

Issue

Vol. 28 No. 1 (2024): 28(1) 2024

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.