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#.

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.
Drop files here or click to browse
JPG · PNG · WebP · up to 500 files · max 4.5 MB each
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
// 💰 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.
You May Also Like
Related tutorials, platform guides, and comparisons
Node.js License Plate OCR API
Node.js License Plate OCR SDK tutorial. Upload an image for a free test! Accurately extract global license plates, native scripts, colors, and vehicle types.
PHP License Plate OCR API
PHP License Plate OCR tutorial. Upload an image for a free test! Accurately extract global license plates, native scripts, colors, and vehicle types.
Python License Plate OCR API
Python License Plate OCR SDK tutorial. Upload an image for a free test! Accurately extract global license plates, native scripts, colors, and vehicle types.
Go License Plate OCR API
Golang License Plate OCR tutorial. Upload an image for a free test! Accurately extract global license plates, native scripts, colors, and vehicle types.
Java License Plate OCR API
Java License Plate OCR tutorial. Upload an image for a free test! Accurately extract global license plates, native scripts, colors, and vehicle types.
C# Invoice OCR API
Upload an image for a free test! Integrate a high-accuracy Invoice OCR API into your C# application. Get structured JSON output for line items, totals, and merchant data. Eliminate Tesseract errors.
Australia Passport OCR with Python SDK
Use the official StructOCR Python SDK and FastAPI to extract structured MRZ and VIZ data from Australia passports with a server-side integration.
Argentina Passport OCR with Python SDK
Use the official StructOCR Python SDK and FastAPI to extract structured MRZ and VIZ data from Argentina passports with a server-side integration.
Argentina DNI OCR Python SDK
Python Tutorial: Automate KYC in Argentina. Extract Spanish text, CUIL/CUIT, and validate TD1 MRZ from DNI using StructOCR Python SDK.
Algeria Passport OCR with Python SDK
Use the official StructOCR Python SDK and FastAPI to extract structured MRZ and VIZ data from Algeria passports with a server-side integration.
Technical Comparisons & Integrations
Explore platform integrations and competitive analysis
Single-Page MRZ SDKs vs. Dual-Page Indian KYC API
Why traditional MRZ scanners fail at full Indian Passport verification, and how to process both the front identity page and the back address page in a single API call.
Template-Based OCR vs. StructOCR API for Invoice Processing
Why traditional zonal/template-based OCR fails at processing vendor invoices, and how layout-agnostic AI APIs instantly extract line items and totals.
Tesseract & PassportEye vs. StructOCR Passport API
A technical evaluation for developers deciding between open-source MRZ scanners and a dedicated cloud-based Passport OCR API.
Tesseract OCR vs. StructOCR API for ISO 6346 Container Numbers
A technical comparison for developers evaluating open-source Tesseract vs. a dedicated cloud API for extracting shipping container numbers.
Add Container OCR to Your v0 App in 5 Minutes
Step-by-step guide to integrating the StructOCR shipping container API into a v0 by Vercel app. Build logistics and yard management tools with zero backend.
Add Driver's License OCR to Your v0 App in 5 Minutes
Step-by-step guide to integrating the StructOCR Driver's License scanner API into a v0 by Vercel app. Build car rental and mobility onboarding flows with zero backend.
From tutorial to production in 5 minutes.
You've seen the code. Now get your API key, grab your 200 free credits, and see it work with your own images. No credit card required.