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Egyptian ID Card Recognition System – AI-Powered OCR & Fraud Detection

A Python-based AI application for detecting, processing, and verifying Egyptian ID cards using YOLO and EasyOCR.

Key Features

🔹 AI-Powered ID Detection – Automatically detects and crops Egyptian ID cards from images.
🔹 Advanced OCR (Optical Character Recognition) – Extracts Arabic and English text from ID cards using EasyOCR.
🔹 Field Extraction & Data Processing – Captures essential details, including:

  • Full Name
  • Address
  • National ID Number
  • Birth Date
  • Governorate
  • Gender
  • Birth Place
  • Location
  • Nationality

🔹 Fraud Detection System – Detects fake IDs by verifying the authenticity of the ID photo and personal details.
🔹 Web Interface with Streamlit – Provides a user-friendly dashboard for seamless ID card processing.

How It Works

1️⃣ Upload an Image – Use the web interface to upload an Egyptian ID card.
2️⃣ AI-Powered Detection – The system detects and extracts ID information.
3️⃣ ID Decoding & Verification – Deciphers ID numbers and flags potential fraudulent documents.
4️⃣ Results Displayed – View structured data, extracted text, and fraud detection status.

Installation Guide

  1. Clone the repository: 
    git clone https://github.com/NASO7Y/ocr_egyptian_ID.git
  2. Navigate to the project directory: 
    cd ocr_egyptian_ID
  3. Create a virtual environment (recommended): 
    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts�ctivate
  4. Install dependencies: 
    pip install -r requirements.txt
  5. Run the application: 
    streamlit run APP.py

Model Training

  • YOLO Object Detection – Trained for Egyptian ID card detection.
  • EasyOCR – Used for high-accuracy text recognition in Arabic and English.

Why Choose This System?

✅ High Accuracy – Advanced deep learning models ensure precise ID recognition.
✅ Fraud Detection – Protects against fake IDs by verifying images and personal details.
✅ Fast & Automated – AI speeds up document processing with minimal human effort.
✅ User-Friendly Web Interface – Easy-to-use Streamlit dashboard for seamless operation.

Acknowledgments

This project utilizes:

Contribute to the Project

Contributions are welcome! Fork the repository and submit a pull request with improvements. Make sure your code meets project standards and includes tests.

Contact & Support

For questions or feedback, feel free to open an issue or reach out to NASO7Y.

Email: [email protected]

LinkedIn: LinkedIn