Egypt Passport OCR with the StructOCR Python SDK

Challenges with Egypt Passport Verification

Egyptian passports, like many official documents, present unique challenges for automated data extraction. Issues such as reflective laminate coatings, complex background security patterns, and variations in print quality can significantly hinder accuracy. Overcoming these obstacles is crucial for any reliable identity verification process, and a robust passport extraction api is essential.

Why StructOCR for Egypt Passports

StructOCR's advanced OCR technology is specifically tuned to handle the nuances of Egyptian passports, ensuring unparalleled accuracy in data extraction. Our system is designed to overcome common issues like glare and complex designs, providing reliable results for your needs. We offer a highly effective passport extraction api and are a leading provider of fintech identity verification software. For the fastest Python integration, install the official StructOCR SDK and see the Python SDK documentation.

Built for High-Compliance Industries

• Travel & Aviation: Our technology serves as an effective [verification solution for travel], significantly speeding up check-in and boarding processes for Egyptian citizens by instantly validating travel documents.
• Financial Services: Leverage our [fintech identity verification software] to streamline customer onboarding, enhance fraud prevention, and ensure regulatory compliance during the KYC process.

Egypt Passport OCR with the Python SDK

The official Python SDK handles file encoding, API communication, and structured passport results. Use the SDK directly or open the FastAPI tab for a server endpoint. Keep your API key in STRUCTOCR_API_KEY.

Prerequisite: `pip install structocr`; set the server-side `STRUCTOCR_API_KEY` environment variable.

Prefer another stack? Open the Node.js SDK + Express integration.

import os
from structocr import StructOCR

# Initialize StructOCR Client
client = StructOCR(os.environ["STRUCTOCR_API_KEY"])

def scan_egypt_passport():
    image_path = "egypt_passport_sample.jpg"

    try:
        print(f"Scanning {image_path}...")
        result = client.scan_passport(image_path)

        if result.get('success'):
            data = result['data']
            print("✅ Passport Extraction Successful!")
            print(f"Passport #:  {data.get('passport_number')}")
            print(f"Name:        {data.get('given_names')} {data.get('surname')}")
            print(f"Nationality: {data.get('nationality')}")
            print(f"DOB:         {data.get('date_of_birth')}")
        else:
            print(f"❌ Extraction Failed: {result.get('error')}")

    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    scan_egypt_passport()

JSON Response Example

The Python SDK returns a dictionary matching this normalized JSON structure.

{
  "success": true,
  "data": {
    "type": "passport",
    "country_code": "EGY",
    "nationality": "EGY",
    "passport_number": "A12345678",
    "surname": "HASSAN",
    "given_names": "AHMED",
    "sex": "M",
    "date_of_birth": "1988-03-12",
    "place_of_birth": "CAIRO",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2025-03-11",
    "issuing_authority": "MINISTRY OF INTERIOR"
  }
}