The Best PHP Library for VIN (Vehicle Identification Number) OCR

The Problem with VIN (Vehicle Identification Number) Parsing

Extracting data from Vehicle Identification Numbers (VINs) presents unique challenges. VINs are often printed on curved surfaces like windshields, leading to perspective distortion. Windshield glare and reflections can obscure the VIN. Dot-matrix fonts, holograms, and variations in VIN layout further complicate the process. Regular expressions and template-based approaches struggle with these complexities, resulting in low accuracy and unreliable data extraction.

The StructOCR Solution

StructOCR utilizes advanced AI and deep learning models specifically trained on VIN images to overcome these challenges. Our solution automatically deskews images, performs smart cropping to focus on the relevant area, and accurately performs iso 3779 compliant extraction even from challenging images with glare, curved surfaces, or non-standard layouts. We provide a standardized JSON output, ensuring easy integration into your applications and meeting soc-2 compliance requirements.Not ready to write code just yet? Upload a sample image to our online vehicle VIN scanner to see how it handles glare and distortion in real-time.

Common Use Cases

• Insurance & Warranty: Accelerate policy quotes and claims by instantly capturing vehicle details.
• Fleet Management: Automate vehicle onboarding and inventory tracking for logistics companies.
• Auto Service & Parts: Ensure accurate parts ordering and error-free vehicle check-ins.

Implementation: Raw API Request

Complete, runnable code to extract data from a VIN (Vehicle Identification Number).

Prerequisite: PHP 7.4+ with cURL

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

package main

<?php

$imagePath = '/path/to/your/vin_image.jpg'; // Replace with the actual path to your image
$apiKey = 'YOUR_API_KEY'; // Replace with your actual API key

// 1. Read the image file and encode it to Base64
$imageData = file_get_contents($imagePath);
if ($imageData === false) {
    die('Failed to read image file.');
}
$base64Image = base64_encode($imageData);

// 2. Prepare the API request payload
$payload = json_encode(['img' => $base64Image]);

// 3. Initialize cURL session
$ch = curl_init('https://api.structocr.com/v1/vin');

// 4. Configure cURL options
curl_setopt_array($ch, [
    CURLOPT_POST => true,
    CURLOPT_POSTFIELDS => $payload,
    CURLOPT_RETURNTRANSFER => true,
    CURLOPT_HTTPHEADER => [
        'x-api-key: ' . $apiKey,
        'Content-Type: application/json'
    ],
]);

// 5. Execute the API request
$response = curl_exec($ch);

// 6. Check for cURL errors
if (curl_errno($ch)) {
    die('cURL error: ' . curl_error($ch));
}

// 7. Close cURL session
curl_close($ch);

// 8. Decode the JSON response
$decodedResponse = json_decode($response, true);

// 9. Handle the API response
if ($decodedResponse === null) {
    die('Failed to decode JSON response: ' . $response);
}

if ($decodedResponse['success']) {
    $vin = $decodedResponse['data']['vin'];
    $confidence = $decodedResponse['data']['confidence'];

    echo "VIN: " . $vin . "\n";
    echo "Confidence: " . $confidence . "\n";

} else {
    echo "Error: " . $decodedResponse['error'] . "\n";
}


?>

Sample JSON Response

The API returns a clean JSON object with normalized fields.

{
  "success": true,
  "data": {
    "vin": "1HGCM82633A004352",
    "confidence": "High",
    "carrier_type": "windshield"
  }
}