A Deep Learning Approach for Helmet Detection and Fine Generation System

Sulbha Yadav, Sumit Singh, Dhruv Bedare and Ishan Samel
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Sulbha Yadav: Department of Computer Engineering, Lokmanya Tilak College of Engineering, Navi Mumbai, India
Sumit Singh: Department of Computer Engineering, Lokmanya Tilak College of Engineering, Navi Mumbai, India
Dhruv Bedare: Department of Computer Engineering, Lokmanya Tilak College of Engineering, Navi Mumbai, India
Ishan Samel: Department of Computer Engineering, Lokmanya Tilak College of Engineering, Navi Mumbai, India

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 4, 902-910

Abstract: Traffic law violations, especially helmet non-compliance among motorcyclists, are a leading cause of road casualties in countries like India. This study proposes a real-time deep learning-based helmet detection and fine generation system that leverages YOLOv3 for object detection and OpenCV with OCR for license plate recognition. The system processes surveillance footage to detect violations and automatically generates e-challans by integrating with vehicle databases. Experimental results show an accuracy of over 95% for helmet detection. This automated solution reduces manual workload, supports road safety enforcement, and has the potential for integration into smart city infrastructure. Future work may involve multilingual plate recognition and improved database interoperability.

Date: 2025
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