Research Article
Automated Helmet Detection and Number Plate Recognition Using YoloV11 and OCR: A Safe Ride Initiative
@INPROCEEDINGS{10.4108/eai.28-4-2025.2358110, author={P. Sowmya and V. Lasya Priya and T. Sai Charan and Venkata Ratnam Kolluru}, title={Automated Helmet Detection and Number Plate Recognition Using YoloV11 and OCR: A Safe Ride Initiative}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part II}, publisher={EAI}, proceedings_a={ICITSM PART II}, year={2025}, month={10}, keywords={helmet infractions number plate recognition optical character recognition (ocr) traffic violations and you only look once (yolov11)}, doi={10.4108/eai.28-4-2025.2358110} }- P. Sowmya
V. Lasya Priya
T. Sai Charan
Venkata Ratnam Kolluru
Year: 2025
Automated Helmet Detection and Number Plate Recognition Using YoloV11 and OCR: A Safe Ride Initiative
ICITSM PART II
EAI
DOI: 10.4108/eai.28-4-2025.2358110
Abstract
Motorcycles are the most popular form of transportation because they are reasonably priced and require little upkeep. The government has mandated that two-wheeler drivers wear helmets when operating a motor vehicle, as per section 129 of the Motorcycle Vehicle Act. Still, many people who break traffic laws do not follow them. Traffic cops manually keep an eye on motorcycle riders at intersections in the majority of developing nations. We suggest an automated system that recognizes motorbike number plates for enforcement and detects helmet infractions in order to solve this problem. First, the You Only Look Once (YOLO) algorithm is used by the system to identify motorbikes in the picture or live video. This algorithm is used again to determine whether the driver is helmeted or not for the motorbikes that were found. Optical Character Recognition (OCR) is used to extract the characters from the motorbike’s number plate after it has been detected for identified motorcycle riders who are not wearing helmets. The YOLOv11 algorithm is utilized for its accuracy and real time object detection. The system aims to automate traffic violations detection in case of not wearing a helmet and number plate recognition from the vehicles.
