An Innovation Approach for Detection of Helmet and Number Plate

A major cause of fatalities in motorcycle accidents is riders not wearing helmets. Conventionally, helmet compliance is monitored by traffic police at intersections or through manual analysis of CCTV footage, both of which demand considerable human effort. The proposed system overcomes these limitations by automatically analysing CCTV videos to detect motorcyclists who are not wearing helmets and extracting their license plate details. First, moving objects are classified as motorcycles or other vehicles. The system then checks whether motorcycle riders are wearing helmets. For riders without helmets, OCR is used to read the vehicle’s license plate number, which also supports theft detection. Using the YOLOv5 algorithm, the system accurately detects helmet usage and license plates in real time. It can also cross-check vehicles against a database to identify stolen ones. When a violation is detected, a digital fine and notification are sent to the vehicle owner, while stolen vehicles trigger instant alerts to both the owner and law enforcement, making the system effective for traffic enforcement and vehicle security.