Traffic Surveillance: An Integrated Approach for Helmet and Number Plate Detection

Abstract

An integrated system for helmet and number plate detection, aimed at enhancing traffic monitoring and law enforcement. Utilizing advanced computer vision, machine learning, and optical character recognition (OCR) techniques, the system automates the identification of motorcyclists without helmets while accurately recognizing vehicle number plates in real time. Designed to operate effectively under diverse environmental conditions, this approach minimizes the reliance on manual traffic surveillance, improves enforcement efficiency, and strengthens road safety measures. The system is scalable and can be integrated into broader smart city infrastructures, providing real-time data for traffic regulation and management. By automating safety compliance checks, this solution promotes adherence to traffic laws and contributes to safer road environments through intelligent surveillance technology.