Automatic Number Plate Detection for Motorcyclists Riding Without Helmet

¹ Department of CSBS, GRIET, Hyderabad, Telangana State, India
² Uttaranchal Institute of Technology, Uttaranchal University, Dehradun, 248007, India
³ KG Reddy College of Engineering & Technology, Hyderabad, India

^* Corresponding author: mamidi.kirankumar09@gmail.com

Abstract

The increased usage of motorcycles in recent times has resulted in a rise of road accidents and injuries, with the absence of helmets being a major contributing factor. The current process of physically checking helmet usage at junctions or using CCTV footage to detect motorcyclists without helmets is time-consuming and requires human intervention. To address this issue, a computerized model is proposed to automatically detect motorcycle riders wearing helmets from images. The proposed model utilizes the You Only Look Once (YOLO) Darknet deep learning framework, which is customized to detect riders with and without helmets. The model also automates an alert to the rider found without a helmet. The dataset consists of a large collection of images with 80 different object categories, covering a wide range of real-world scenarios. The solution has the potential to enhance the capabilities of ANPR systems for traffic management, parking management, law enforcement etc.