UAE Emirates ID OCR Python SDK
Instantly extract data, bilingual text, and MRZ from UAE Emirates IDs (Front & Back) using our native Python library.

Parsing Emirates ID Challenges
Parsing the UAE Emirates ID presents unique challenges for global businesses. The documents feature complex bilingual layouts containing both Arabic and English text. Additionally, managing dual-sided verification, extracting the 15-digit national identification number, and parsing the 3-line Machine Readable Zone (MRZ) on the reverse side require highly specialized OCR capabilities.
Why StructOCR for the UAE
StructOCR's model is specifically trained on a vast dataset of UAE Emirates IDs, ensuring high accuracy across both Arabic and Latin scripts. This advanced national id ocr capability facilitates efficient information parsing for Gulf region compliance. Fully supports the latest Emirates ID formats, enabling seamless data extraction from both front and back sides, specifically optimized for the 3-line MRZ on the back. Our latest v1.4.0 Python SDK simplifies the integration process, allowing you to extract structured data in seconds.
Common Use Cases in the UAE
- Fintech & Crypto Onboarding: Verify users for trading apps and digital wallets in Dubai and Abu Dhabi.
- Real Estate (Ejari): Automate tenant identity verification for property management.
- Telecom & Utilities: Speed up SIM card registration and utility service applications.
Live Demo: ID card scanner
No registration required. Upload a file to test the extraction.
Drop files here or click to browse
JPG · PNG · WebP · up to 500 files · max 4.5 MB each
Python SDK Integration
Install the SDK via pip: `pip install structocr`. Then use the following code.
Prerequisite: Python 3.6+ and `structocr` v1.4.0+ library installed.
Prefer another stack? Open the Node.js SDK + Express integration.
from structocr import StructOCR
# 💰 Deposit via Crypto (USDT/USDC) for a 10% credit bonus!
# 👉 https://structocr.com/pricing
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")
def scan_emirates_id():
# Note: Supports JPG, PNG, WebP (Max 4.5MB)
# Target: Emirates ID (Supports front, back, and 3-line MRZ)
image_path = "uae_emirates_id_back.jpg"
try:
print(f"Scanning {image_path}...")
# The SDK handles file upload and API communication
# It automatically detects that this is a UAE document
result = client.scan_national_id(image_path)
# Check success flag
if result.get('success'):
data = result['data']
print("✅ UAE Emirates ID Extraction Successful!")
# Basic Identity
print(f"Region: {data.get('country_code')}")
print(f"Name: {data.get('given_names')} {data.get('surname')}")
print(f"Card Number: {data.get('document_number')}")
# Critical Field: UAE Identity Number (15 digits)
print(f"Personal #: {data.get('personal_number')}")
# Demographics
print(f"DOB: {data.get('date_of_birth')} ({data.get('sex')})")
print(f"Nationality: {data.get('nationality')}")
# Machine Readable Zone (MRZ) - Found on the back
additional = data.get('additional_fields', {})
if additional.get('mrz_line_1'):
print("\n--- MRZ Data (Reverse Side) ---")
print(additional.get('mrz_line_1'))
print(additional.get('mrz_line_2'))
if additional.get('mrz_line_3'):
print(additional.get('mrz_line_3'))
else:
print(f"❌ Extraction Failed: {result.get('error')}")
except Exception as e:
# Handle SDK or Network errors
print(f"An error occurred: {e}")
if __name__ == "__main__":
scan_emirates_id()Technical Specs
- •Latency: < 3s (Average via Cloudflare edge routing)
- •Uptime: 99.9% SLA
- •Security: AES-256 Encryption & GDPR/PDPL Compliant
- •Input: JPG, PNG, WebP (Max 4.5MB) — Supports Front & Back images
- •Output: JSON (Structured Data with 3-line MRZ support)
Key Features
- •Bilingual Arabic & English: Native support for rendering and extracting dual-language fields accurately.
- •15-Digit ID Formatting: Automatically validates and formats the 784-YYYY-XXXXXXX-X personal number pattern.
- •3-Line MRZ Parsing: Accurately extracts and validates the Machine Readable Zone lines standard on Emirates IDs.
- •Blur & Glare Detection: Automatically identifies unreadable images caused by smart card holograms.
- •Smart Crop & Deskew: Automatically aligns and crops the document from complex backgrounds.
JSON Response Example
The SDK returns a Python dictionary matching this JSON structure.
{
"success": true,
"data": {
"type": "national_id",
"country_code": "ARE",
"nationality": "ARE",
"document_number": "123456789",
"card_series": null,
"personal_number": "784-1990-1234567-1",
"surname": "AL MANSOORI",
"given_names": "AHMED MOHAMMED",
"sex": "M",
"date_of_birth": "1990-05-15",
"place_of_birth": "DUBAI",
"address": "Downtown Dubai, Sheikh Mohammed bin Rashid Blvd",
"date_of_issue": "2021-08-20",
"date_of_expiry": "2031-08-19",
"issuing_authority": "Federal Authority for Identity and Citizenship",
"additional_fields": {
"phone_number": null,
"tramite_number": null,
"ejemplar": null,
"mrz_line_1": "IDARE1234567894<<<<<<<<<<<<<<<",
"mrz_line_2": "9005155M3108198ARE<<<<<<<<<<<4",
"mrz_line_3": "AL<MANSOORI<<AHMED<MOHAMMED<<<"
}
}
}Frequently Asked Questions
Does the API support Arabic text extraction?
Yes, our engine is natively trained to handle the Arabic scripts present on the Emirates ID.
Are the ID images stored on your servers?
No. All images are processed securely in-memory and are discarded immediately after the JSON response is generated.
Can I pay for API credits using Cryptocurrency?
Yes! StructOCR supports USDT/USDC deposits. You also get an automatic 10% credit bonus when topping up with crypto.
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