Indian Passport Family Details OCR

Automate background checks and visa applications by securely and accurately extracting family lineage and relationship data from Indian passport bottom pages.

Parsing family details like Father, Mother, and Spouse names from an Indian passport back page.

The Bottleneck in Background Verification

Background verification (BGV) agencies, immigration consultants, and visa processors spend countless hours manually typing out Father, Mother, and Spouse names from passport scans. The proximity of these fields to the address block and varying label structures often confuse generic OCR systems, causing data spillage across fields. Discover how we solve these complexities globally in our travel identity verification solutions.

StructOCR: Precision Relationship Parsing

Powered by our core Passport OCR engine, our dedicated relationship module isolates the exact line items for family members, ignoring surrounding noise. Deployed on secure Cloudflare edge nodes with a strict process-and-forget architecture, StructOCR delivers precise JSON key-value pairs for lineage data while ensuring zero data retention, radically accelerating the pre-processing phase for visa applications.

Live Demo: Passport scanner

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Core Industry Applications

Corporate Background Checks (BGV)

Automate the data entry phase of employee screening globally. We support borderless USDT/Crypto payments for international SaaS operators. View our straightforward API pricing.

Visa & Immigration Processing

Auto-populate complex DS-160 or Schengen visa application forms with accurate family details extracted in milliseconds.

Matrimonial & Dating Verification

Verify family details for premium tier users on trust-based platforms seamlessly, keeping sensitive data off public cloud storage.

Educational Admissions

Streamline university admissions for international Indian students by parsing required parental data automatically via pure API calls.

Technical Specs

  • Field Isolation: Advanced NLP logic to accurately separate closely printed parent names from preceding labels.
  • Null Handling: Safely returns null for absent fields (e.g., unmarried individuals with no spouse listed).
  • Base64 & File Native: Designed for server-to-server data streams, keeping PII completely off public URLs.
  • Cloudflare Routing: Ensures high availability, low latency, and strict zero-data-retention processing.

Key Features

  • Father Name Extraction: Accurate capture ignoring preceding labels and noise.
  • Mother Name Extraction: Reliable extraction even in tightly packed, poorly aligned layouts.
  • API-First Architecture: Pure HTTP integration completely eliminates SDK bloat and version conflicts.

Integration & AI Prompts

StructOCR is API-first, eliminating the need for bulky SDKs. Extract specific family nodes directly from the JSON response using raw files or Base64 strings. See our Passport OCR Developer Documentation for full schema details.

import requests
import base64

# 📚 Developer Docs: https://structocr.com/developers/passport-ocr

# Note: StructOCR is strictly API-first. It natively supports File Uploads,
# Base64-encoded strings, and direct Image URLs without requiring an SDK.

with open("passport_family.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

url = "https://api.structocr.com/v1/passport/india/back-page"
headers = {
    "x-api-key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "img": base64_image
}

try:
    # Processed in-memory at the edge with zero data retention
    print("Extracting Family Details...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        print("✅ Family Details Extracted!\n")
        
        # Core identity context
        core = result['data']
        print(f"Applicant: {core.get('given_names')} {core.get('surname')}")
        
        # Deep family linkage from the back page
        family = core['country_specific']['last_page']
        print(f"Father:    {family.get('father_name')}")
        print(f"Mother:    {family.get('mother_name')}")
        print(f"Spouse:    {family.get('spouse_name', 'N/A')}")
    else:
        print(f"❌ Extraction Failed: {result.get('error')} - {result.get('message')}")
except Exception as e:
    print(f"Error: {e}")

Standardized JSON Output

Receive clean key-value pairs for family lineage, perfectly formatted for your database schema.

{
  "success": true,
  "data": {
    "type": "passport",
    "country_code": "IND",
    "nationality": "INDIAN",
    "passport_number": "Z1234567",
    "surname": "SHARMA",
    "given_names": "RAHUL",
    "sex": "M",
    "date_of_birth": "1988-07-22",
    "place_of_birth": "NEW DELHI",
    "date_of_issue": "2021-04-10",
    "date_of_expiry": "2031-04-09",
    "issuing_authority": "MINISTRY OF EXTERNAL AFFAIRS",
    "country_specific": {
      "last_page": {
        "father_name": "AMIT SHARMA",
        "mother_name": "SITA SHARMA",
        "spouse_name": "PRIYA SHARMA",
        "address": "FLAT 4B, GREENWOOD APARTMENTS, NEW DELHI PIN: 110001, INDIA",
        "old_passport_number": "P7654321",
        "old_passport_issue_date": "2010-01-05",
        "old_passport_issue_place": "DELHI",
        "file_no": "DL1076071103622",
        "ecr_status": null
      }
    }
  }
}

Frequently Asked Questions

Do you provide an SDK for mobile integration?

StructOCR is intentionally designed as an API-first platform rather than providing proprietary SDKs. This allows you to use your preferred language wrappers and eliminates app size bloat, while natively supporting file uploads and Base64 directly from your backend.

What happens if a field (like spouse name) is blank on the passport?

The API dynamically detects missing fields and will return a null for that specific JSON key, ensuring your application schema remains intact without throwing errors.

Does it process both Hindi and English text?

Currently, our engine is highly optimized for the English printed text on the document, which serves as the primary standardized data point for global BGV and immigration processing systems.

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Technical Comparisons & Integrations

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