Helfine: Real-Time Helmet Violation Detection with Automated Fine System

<p>Motorcycles have traditionally been one of the most widely used modes of transportation in developing countries. However, in recent times, the number of motorcycle accidents has increased. One of the major contributing factors to these accidents is the absence of helmets worn by riders. Traffic authorities monitor road intersections, review CCTV footage, and take action against motorcyclists who fail to comply with helmet regulations. Enforcing this rule typically requires human intervention, making it a labor-intensive process. To address this issue, this project proposes an automated system that detects and extracts motorcycle number plates from riders without helmets using CCTV footage. The extracted number plate is then processed using an Optical Character Recognition (OCR) algorithm to identify the vehicle’s registration details. This AI- powered approach helps in identifying violators and notifying them to pay their challans. The proposed system first captures real-time traffic images before distinguishing motorcycles from other vehicles on the road.</p>