Vehicle Number Plate Recognition System
Vehicle Number Plate Recognition System
AI-Based Automatic Number Plate Recognition (ANPR)
Problem Statement
Manual vehicle identification in parking lots, toll booths, and traffic surveillance is inefficient and error-prone. Traditional systems fail to accurately recognize number plates in varying lighting, angles, and speeds.
Solution Overview
The Vehicle Number Plate Recognition System uses computer vision and OCR models to detect vehicles, localize number plates, and extract plate text in real time, enabling automated monitoring, access control, and vehicle tracking.
Key Features
Core Features
- • Real-time number plate detection
- • High-accuracy OCR extraction
- • Works in low light & varied angles
- • Multi-country plate support
Admin & System Features
- • Vehicle entry/exit logging
- • Searchable plate database
- • Blacklist & whitelist alerts
- • Analytics & reporting dashboard
System Architecture
Camera Feed
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Vehicle Detection Model
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Number Plate Localization
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OCR Text Extraction
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Database & Alerts
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Dashboard / API
Technology Stack
Computer Vision
OpenCV, YOLO, Deep Learning Detection Models
OCR & AI
Tesseract OCR, Custom CNN & Transformer Models
Backend Services
Python, FastAPI, REST APIs
Frontend Dashboard
HTML, Tailwind CSS, Data Visualization
Database
PostgreSQL, Image & Event Storage
Deployment & Edge
Docker, Cloud & Edge Device Integration
Use Cases
- • Smart parking and access control
- • Toll booth automation
- • Traffic surveillance and monitoring
- • Gated community security
- • Law enforcement vehicle tracking
- • Logistics and fleet management
Business Impact
By automating vehicle identification and monitoring, the system reduces manual intervention, enhances security, and enables scalable intelligent transportation solutions. Organizations benefit from improved operational efficiency, regulatory compliance, and real-time visibility across vehicle movement data.