ALPR license plate recognition system showing live multi-camera feed with YOLO11 detection boxes highlighting Italian license plates, OCR text conversion with 98.5% accuracy metrics, real-time transit log, and edge computing latency indicators under 100ms
ML & Recognition

ALPR System

License Plate Recognition

98.5%
Accuracy
<100ms
Latency
€200-300
Camera Cost
50k+
Training Photos

Overview

A system that automatically reads license plates from cameras. Used by parking lots, restricted traffic zones, and security systems to know who enters and exits. The problem? Commercial cameras cost €5k-10k each and are closed systems.

I developed a custom system that works with normal IP cameras (€200-300) and recognizes plates with 98.5% accuracy. The AI (YOLO11) is trained on 50k+ photos of Italian plates in every condition: night, rain, dirty, angled. The system reads the plate, converts it to text (OCR), and automatically corrects typical errors (0 vs O, 8 vs B).

Flexible architecture: either central server processing recorded video, or mini-computer on the camera (edge computing) processing in real-time with <100ms latency. Handles multiple cameras simultaneously. Web dashboard to see transits, manage white/black lists (e.g., parking subscribers), and statistics.

Use cases: parking lots with automatic barriers, restricted zone access control, condos with resident lists, warehouses tracking vans.

Key Features

  • 98.5% accuracy plate recognition with AI trained on 50k+ Italian photos
  • Works with normal IP cameras (€200-300) instead of proprietary systems (€5k-10k)
  • Automatic ambiguous character correction (0/O, 8/B, 1/I) using Italian plate patterns
  • Flexible architecture: central server or edge computing <100ms on camera

Technologies Used

YOLO11OCREdge ComputingReal-time