The Best C# API for Global License Plate OCR (Free Image Testing)

Deploy automated license plate recognition (ALPR) built for global scale. Upload a vehicle image for a free test today and extract native scripts and multi-plate layouts seamlessly using C#.

Global License Plate OCR extraction process diagram
StructOCR transforms raw vehicle images into validated JSON with native script retention.

The Problem with Global ALPR Parsers in C#

Enterprise .NET/C# applications often struggle with legacy ALPR libraries that are optimized only for standard Latin alphabets. These traditional tools fail when encountering complex layouts from the Middle East or Asia, and struggle to accurately extract native scripts (Arabic, Cyrillic, Thai, Chinese). Furthermore, generic models often lack the ability to process multi-plate setups, like tractor-trailer configurations, or identify secondary data such as plate colors and vehicle types.

The StructOCR Solution

StructOCR allows your .NET backend to offload complex vehicle image processing to our specialized deep learning models. Our API transcends generic models by accurately extracting native scripts worldwide exactly as printed. By returning validated JSON directly to your C# application, you can easily integrate multi-dimensional attributes—including plate numbers, vehicle types, and country inferences—into your global logistics and tolling workflows. Explore our flexible pricing to scale your production environment seamlessly.

Common Use Cases

  • Toll Collection & Parking: Automate entry and exit gates globally by capturing primary plate numbers and vehicle classifications instantly.
  • Global Logistics & Border Control: Track multi-plate configurations (e.g., stacked trailer and prime mover plates) simultaneously across international borders.
  • Law Enforcement: Cross-reference vehicle types and plate colors to detect unregistered or commercial vehicles dynamically.

Live Demo: License Plate OCR Scanner

No registration required. Upload a file to test the extraction.

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Implementation: Raw API Request

Complete, runnable C# code to encode a vehicle image in Base64 and extract license plate data. For other language examples and deep parameter explanations, visit the full License Plate OCR API Reference.

Prerequisite: .NET Core 3.1+ or .NET 5+ and System.Text.Json

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

using System;
using System.IO;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;

namespace StructOCR_Client
{
    class Program
    {
        static async Task Main(string[] args)
        {
            string apiKey = "YOUR_API_KEY"; // Replace with your actual API key
            string imagePath = "path/to/your/vehicle_image.jpg"; // Replace with the path to your image

            // 1. Read image and encode to Base64
            byte[] fileBytes = File.ReadAllBytes(imagePath);
            string base64Img = Convert.ToBase64String(fileBytes);

            // 2. Create JSON payload
            var payload = new { img = base64Img };
            string jsonPayload = JsonSerializer.Serialize(payload);

            // 3. Build the HTTP request (Requires application/json)
            using var client = new HttpClient();
            using var request = new HttpRequestMessage(HttpMethod.Post, "https://api.structocr.com/v1/license-plate");
            
            request.Headers.Add("x-api-key", apiKey);
            request.Content = new StringContent(jsonPayload, Encoding.UTF8, "application/json");

            Console.WriteLine("Uploading Base64 image to StructOCR API...");

            // 4. Send the request and receive the response
            HttpResponseMessage response = await client.SendAsync(request);
            string responseBody = await response.Content.ReadAsStringAsync();

            // 5. Parse the JSON response
            using JsonDocument doc = JsonDocument.Parse(responseBody);
            JsonElement root = doc.RootElement;

            // 6. Extract the License Plate data
            if (root.TryGetProperty("success", out JsonElement successVal) && successVal.GetBoolean())
            {
                JsonElement data = root.GetProperty("data");
                Console.WriteLine("✅ Extraction Successful!");
                Console.WriteLine("Plates Detected: " + data.GetProperty("plates").GetArrayLength());
                
                string countryGuess = data.GetProperty("country_guess").ValueKind == JsonValueKind.Null 
                    ? "N/A" 
                    : data.GetProperty("country_guess").GetString();
                
                Console.WriteLine("Country Guess: " + countryGuess);
                Console.WriteLine("Confidence: " + data.GetProperty("confidence").GetString());
                Console.WriteLine("\n--- Raw Data ---");
                Console.WriteLine(JsonSerializer.Serialize(data, new JsonSerializerOptions { WriteIndented = true }));
            }
            else
            {
                string errorCode = root.TryGetProperty("code", out JsonElement code) ? code.GetString() : "Unknown Code";
                string errorMsg = root.TryGetProperty("message", out JsonElement msg) ? msg.GetString() : "Unknown Error";
                Console.WriteLine($"❌ Error [{errorCode}]: {errorMsg}");
            }
        }
    }
}

Technical Specs

  • Input format: application/json payload with Base64 encoded string
  • File Constraints: Max 4.5MB (decoded), compress to < 300KB for best speed
  • Supported Formats: Standard Data URI schemas, raw Base64 strings (JPG, PNG, WebP)
  • Language Support: Global scripts (Arabic, Chinese, Thai, Cyrillic, etc.)
  • Output: JSON (Multi-dimensional attributes)

Key Features

  • Global Coverage: Optimized for worldwide plates spanning the Middle East, Asia, Europe, and the Americas.
  • Native Script Retention: Extracts local scripts exactly as printed without translation or transliteration.
  • Multi-Plate Parsing: Natively handles extracting multiple plates from a single vehicle (e.g., stacked trailer plates).

Sample JSON Response

The API returns a clean JSON array with details on all detected plates, preserving native characters and strict enums.

{
  "success": true,
  "data": {
    "plates": [
      {
        "plate_number": "TRE 1631M",
        "plate_color": "yellow",
        "plate_type": "trailer"
      },
      {
        "plate_number": "XB 98X",
        "plate_color": "yellow",
        "plate_type": "commercial"
      }
    ],
    "region_text": null,
    "country_guess": "Singapore",
    "confidence": "High"
  }
}

Frequently Asked Questions

How should I encode the image?

Send the image as a Base64 encoded string wrapped in a JSON payload. The Base64 string must not contain any internal whitespaces or newlines.

What is the maximum file size?

The maximum decoded payload restriction is 4.5MB. Exceeding this will trigger a 413 FILE_TOO_LARGE error.

Can it read non-English characters?

Yes. Our engine natively retains and extracts local scripts like Arabic, Thai, and Cyrillic exactly as printed.

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