Automatic Helmet Detection and License Plate Recognition

This project is a real-time computer vision system built to promote road safety by detecting helmet usage among motorcycle riders and extracting vehicle license plate information. Developed as part of an academic project, it processes live video feeds to automatically identify safety violations and log vehicle details for enforcement purposes.

The system uses two lightweight, optimized deep learning models: YOLOv5 for helmet detection and MobileNet-SSD for license plate localization, ensuring fast and accurate performance suitable for real-time applications.

Key Features

Helmet Detection

License Plate Detection

Violation Reporting

Scalable & Modular

Tech Stack

• Python - Core programming language
• YOLOv5 & MobileNet-SSD - Helmet and license plate detection models
• Google Colab & Git - Development and version control tools