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Automatic License Plate Detection and Recognition System
This project implements an Automatic License Plate Recognition (ALPR) system using YOLO11 for object detection and PaddleOCR for text recognition. It processes video streams to detect, track, and recognize license plates in real time, then stores the extracted data in structured Excel reports with timestamps.
Project Overview
This AI-powered ALPR system is designed for real-time vehicle monitoring applications. By combining YOLO11 object detection with PaddleOCR, the system accurately detects license plates, extracts plate numbers, tracks vehicles, and logs results efficiently for further analysis.
Key Features
Real-Time Detection & Tracking
- 🚗 Detects vehicles and license plates in video streams.
- 🆔 Assigns unique tracking IDs to avoid duplicate recognition.
License Plate OCR
- 🔍 Uses PaddleOCR to extract plate numbers.
- 🧠 Preprocesses plate images to improve OCR accuracy.
Region of Interest (ROI) Filtering
- 📐 Detects plates only inside a defined polygon area.
- 🚫 Reduces false detections and irrelevant processing.
Excel-Based Data Logging
- 📊 Saves plate numbers with timestamps.
- 📅 Organizes data into daily Excel sheets.
User Interaction & Visualization
- 🖥️ Displays bounding boxes and tracking IDs in real time.
- 🖱️ Shows mouse coordinates for debugging and calibration.
Technology Stack
- 🐍 Programming Language: Python
- 🎥 Computer Vision: OpenCV
- 🧠 Object Detection: YOLO11 (Ultralytics)
- 🔤 OCR Engine: PaddleOCR
- 📊 Data Storage: Excel (xlwings)
Use Cases
- 🚦 Traffic Law Enforcement – Detect and log violating vehicles.
- 🛣️ Toll Collection Systems – Automate vehicle registration.
- 🅿️ Parking Management – Track entry and exit of vehicles.
- 🏙️ Smart City Surveillance – Monitor vehicle movement via CCTV.
Conclusion
This Automatic License Plate Detection and Recognition System delivers a reliable and scalable solution for real-time vehicle monitoring. By combining YOLO11 detection with PaddleOCR text recognition, the system ensures high accuracy, efficient tracking, and structured data storage, making it ideal for smart transportation and security applications.