Full-Field Mexico Vehicle Registration (Tarjeta de Circulación) OCR

The Challenge: 32 States of Extreme Fragmentation

Mexico presents a 'US-style' OCR challenge for Latin America: extreme fragmentation. The Tarjeta de Circulación is issued at the state level across 32 different entities, meaning there is no national standard layout. Some states use paper cards, others plastic; some mix QR codes with dense text, and fonts vary wildly. Traditional OCR systems that rely on fixed bounding-box templates completely fail here because it is impossible to maintain templates for every state variation. Learn more about our template-free capabilities on our Vehicle Registration OCR product page.

Template-Free Semantic Key-Value Mapping

StructOCR abandons outdated template matching. Our engine uses advanced Large Language Model (LLM) backed semantic parsing to intelligently 'read' the document like a human does. Regardless of the state's layout, it correctly identifies and maps the VIN, Plate, and Make. Universal specs are normalized perfectly, while unique state-specific identifiers are dynamically captured into our `localized.generic.unmapped_fields` object. Discover how this fits into your Latin American automotive workflows in our Vehicle Registration Solutions guide.

Core Industry Applications

Integration & API Documentation

Easily integrate our full-field OCR API. For full technical details, visit our Developer API Documentation.

import requests
import base64

# 📸 Test for free with your own image upload: https://structocr.com/developers/vehicle-registration-ocr

with open("mexico-tarjeta-de-circulacion-full-ocr.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

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

response = requests.post(url, headers=headers, json=payload)
result = response.json()

if result.get('success'):
    data = result.get('data', {})
    std = data.get('standardized', {})
    print("✅ Standardized VIN:", std.get('vin'))
    
    # Mexico specific fields are captured in the generic fallback
    loc = data.get('localized', {})
    if 'generic' in loc and loc['generic'].get('unmapped_fields'):
        unmapped = loc['generic']['unmapped_fields']
        print("✅ Estado:", unmapped.get('estado'))
        print("✅ Folio:", unmapped.get('folio'))

{
  "success": true,
  "data": {
    "document": {
      "country_code": "MX",
      "document_type": "VEHICLE_REGISTRATION",
      "confidence_score": 0.98
    },
    "standardized": {
      "vin": "SAMPLEVIN12345678",
      "plate": {
        "number": "ABC-123",
        "formatted": "ABC 123"
      },
      "make_normalized": "Toyota",
      "year": 2020
    },
    "localized": {
      "generic": {
        "unmapped_fields": {
          "estado": "Ciudad de México",
          "folio": "A12345678",
          "tipo_vehiculo": "Automovil"
        }
      }
    }
  }
}