Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning

Open Access

Year : 2024 | Volume :02 | Issue : 01 | Page : 9-18
By

Anil Kumar Reddy Tetali,

G. R. S Murthy,

  1. Research Scholar, TDR-HUB-Andhra University, Visakhapatnam, India
  2. Professor, Gayatri Vidhya Peeth College Degree PGC(A)Visakhapatnam, Visakhapatnam, India

Abstract

This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent problems of these systems hinder the efficient detection and enforcement of fines on violators. Our proposal suggests a novel approach that integrates helmet detection with license plate recognition to detect and penalize motorcyclists without wearing helmets. Our system utilizes the You Only Look Once (YOLO) object detection technique to detect individuals breaking helmet rules and record their license plate data. The dataset for training contains a variety of photos showing riders wearing helmets and without wearing helmets. The image data was first converted to grayscale and then saved in CSV files. Images are converted to grayscale values during testing and compared with those in the training dataset to improve detection accuracy. We present a new Convolutional Neural Network (CNN) structure specifically created to categorize different types of helmets and identify whether helmets are present or not in photos. This CNN design combines moderate execution speed with strong generalization capabilities, making it an ideal decision support tool for traffic departments. The proposed work is entirely built with Python 3.9, highlighting its versatility and effectiveness. This research enhances road safety by improving the detection and enforcement of helmet-wearing violations through modern technology and procedures, thereby decreasing fatality rates from motorcycle accidents

Keywords: YOLO, CNN model, license plate recognition, helmet detection, motor cyclist, gray scale

[This article belongs to International Journal of Electrical and Communication Engineering Technology(ijecet)]

How to cite this article: Anil Kumar Reddy Tetali, G. R. S Murthy. Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning. International Journal of Electrical and Communication Engineering Technology. 2024; 02(01):9-18.
How to cite this URL: Anil Kumar Reddy Tetali, G. R. S Murthy. Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning. International Journal of Electrical and Communication Engineering Technology. 2024; 02(01):9-18. Available from: https://journals.stmjournals.com/ijecet/article=2024/view=156552

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Regular Issue Open Access Review Article
Volume 02
Issue 01
Received May 21, 2024
Accepted June 19, 2024
Published July 17, 2024
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