Indonesian Vehicle Registration (STNK) OCR

The Disaster of Dot-Matrix Typography

Digitizing the Indonesian Surat Tanda Nomor Kendaraan (STNK) presents a unique optical nightmare: legacy hardware. Today, a massive volume of STNK certificates in Indonesia are still printed using old-school dot-matrix printers. This means the critical Chassis Number (Nomor Rangka) is not a solid, continuous line of ink, but rather a collection of disconnected dots. When these dots fade, misalign, or overlap with the complex anti-counterfeiting security patterns on the paper, standard AI vision models and LLMs fail dramatically. They are trained on continuous typography and simply cannot 'connect the dots.' To see how our engine conquers severe typographical distortion, explore our core OCR product capabilities.

Dot-Reconstruction & Background Bypassing

StructOCR is purpose-built to handle the raw reality of Southeast Asian documentation as a specialized module within our Automotive VIN OCR suite. Our engine utilizes a proprietary dot-interpolation algorithm that mathematically reconstructs fragmented, dot-matrix characters back into solid alphanumeric strings. Simultaneously, adaptive thresholding filters out the heavy security watermarks behind the text. By enforcing strict ISO 3779 validation, we guarantee that the extracted Nomor Rangka is structurally flawless, even if the original print is severely faded.

Core Industry Applications in Indonesia

Integration & AI Prompts

Don't let dot-matrix printers break your onboarding funnel. Integrate our API directly or copy the prompt below into Cursor or v0 to generate your React frontend.

import requests
import base64

# 💰 Save 30%+ vs competitors. Get 200 free credits instantly:
# 👉 https://structocr.com/register

# 1. Prepare Base64 Image of the Indonesian STNK
with open("indonesian_stnk_document.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

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

try:
    print("Scanning Indonesian STNK Document...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        data = result['data']
        print("✅ Extraction Successful!")
        print(f"VIN (Nomor Rangka): {data.get('vin')}")
        print(f"Confidence:         {data.get('confidence')}")
    else:
        print(f"❌ Extraction Failed: {result.get('error')} - {result.get('message')}")

except Exception as e:
    print(f"An error occurred: {e}")

{
  "success": true,
  "data": {
    "vin": "MHFKGN41X00123456",
    "confidence": "High",
    "carrier_type": "document"
  }
}