OCR in C# CodeProject Tutorial: Extract Text from Images with IronOCR

How Do You Install IronOCR in a .NET Project?

The fastest way to add OCR to a .NET 10 project is through the NuGet Package Manager. Open a terminal in your project directory and run the dotnet CLI command, or use the Package Manager Console inside Visual Studio:

# .NET CLI
dotnet add package IronOcr

# Package Manager Console
Install-Package IronOcr

# .NET CLI
dotnet add package IronOcr

# Package Manager Console
Install-Package IronOcr

After installation, the NuGet package manager downloads all required assemblies and wires up references automatically. IronOCR targets .NET Framework 4.6.2+, .NET Core 3.1+, and .NET 5 through .NET 10, so it works across console apps, ASP.NET Core services, WPF applications, and Azure Functions.

You do not need to register a license key to test locally -- a trial watermark appears on output until a license is applied. Add the using directive and, when you are ready for production, pass your key once at startup:

using IronOcr;

// Apply license key before any OCR calls (production only)
IronOcr.License.LicenseKey = "YOUR-LICENSE-KEY";

using IronOcr;

// Apply license key before any OCR calls (production only)
IronOcr.License.LicenseKey = "YOUR-LICENSE-KEY";

See the IronOCR licensing page for pricing and activation details.

How Do You Extract Text from an Image File?

The core OCR workflow involves three objects: IronTesseract (the engine), OcrInput (the input container), and OcrResult (the output). The sample below reads a PNG and prints the recognised text to the console.

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
input.LoadImage("sample-document.png");

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
input.LoadImage("sample-document.png");

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

How Do You Process Scanned Documents and TIFF Files?

Multi-page TIFF files are common in document scanning workflows. IronOCR handles them with LoadImageFrames, which lets you choose exactly which frames (pages) to process -- useful when you only need a subset of a large archive.

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
int[] pageIndices = { 0, 1, 2 };
input.LoadImageFrames("scanned-documents.tiff", pageIndices);

// Correct skew and remove noise before reading
input.Deskew();
input.DeNoise();

OcrResult result = ocr.Read(input);

foreach (var page in result.Pages)
{
    Console.WriteLine($"Page {page.PageNumber}:");
    Console.WriteLine(page.Text);
}

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
int[] pageIndices = { 0, 1, 2 };
input.LoadImageFrames("scanned-documents.tiff", pageIndices);

// Correct skew and remove noise before reading
input.Deskew();
input.DeNoise();

OcrResult result = ocr.Read(input);

foreach (var page in result.Pages)
{
    Console.WriteLine($"Page {page.PageNumber}:");
    Console.WriteLine(page.Text);
}

How Do You Configure Language Support for OCR?

By default, IronOCR reads English text. To process documents in other languages, install the matching language NuGet package and set the Language property on the IronTesseract instance.

dotnet add package IronOcr.Languages.German
dotnet add package IronOcr.Languages.French
dotnet add package IronOcr.Languages.Japanese

dotnet add package IronOcr.Languages.German
dotnet add package IronOcr.Languages.French
dotnet add package IronOcr.Languages.Japanese

Then configure the engine and, for bilingual documents, add a secondary language:

using IronOcr;
using IronOcr.Languages;

var ocr = new IronTesseract();
ocr.Language = OcrLanguage.German;

// For bilingual documents (e.g. Canadian forms, EU directives)
ocr.AddSecondaryLanguage(OcrLanguage.French);

using var input = new OcrInput();
input.LoadImage("german-invoice.png");

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

using IronOcr;
using IronOcr.Languages;

var ocr = new IronTesseract();
ocr.Language = OcrLanguage.German;

// For bilingual documents (e.g. Canadian forms, EU directives)
ocr.AddSecondaryLanguage(OcrLanguage.French);

using var input = new OcrInput();
input.LoadImage("german-invoice.png");

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

IronOCR supports over 125 languages, each distributed as a separate lightweight NuGet package. This keeps your production binary small -- only the language data your application actually needs is included. The engine blends primary and secondary language models during recognition when you call AddSecondaryLanguage.

How Do You Handle OCR Errors and Improve Recognition Results?

Production applications need error handling around the OCR pipeline. Image quality issues, missing files, or unsupported formats can cause exceptions. Wrapping the call in a try/catch block gives you a clean recovery path.

using IronOcr;

var ocr = new IronTesseract();
ocr.Language = OcrLanguage.English;

try
{
    using var input = new OcrInput();
    input.LoadImage("document.png");
    input.DeNoise();
    input.Deskew();

    OcrResult result = ocr.Read(input);

    if (result.Text.Length > 0)
    {
        Console.WriteLine("Recognised text:");
        Console.WriteLine(result.Text);
    }
    else
    {
        Console.WriteLine("No text was detected in the image.");
    }
}
catch (Exception ex)
{
    Console.WriteLine($"OCR error: {ex.Message}");
}

using IronOcr;

var ocr = new IronTesseract();
ocr.Language = OcrLanguage.English;

try
{
    using var input = new OcrInput();
    input.LoadImage("document.png");
    input.DeNoise();
    input.Deskew();

    OcrResult result = ocr.Read(input);

    if (result.Text.Length > 0)
    {
        Console.WriteLine("Recognised text:");
        Console.WriteLine(result.Text);
    }
    else
    {
        Console.WriteLine("No text was detected in the image.");
    }
}
catch (Exception ex)
{
    Console.WriteLine($"OCR error: {ex.Message}");
}

A few additional settings that help when accuracy is lower than expected:

• ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.Auto -- lets Tesseract choose between single-column, multi-column, and single-word layouts automatically
• ocr.Configuration.ReadBarCodes = false -- disables barcode detection if you are processing text-only documents and want faster throughput
• ocr.Configuration.TesseractVersion = TesseractVersion.Tesseract5 -- ensures you use the fastest available engine

For structured forms where fields appear at predictable positions, use region-based OCR to read only the areas that matter:

using IronOcr;
using IronSoftware.Drawing;

var ocr = new IronTesseract();

using var input = new OcrInput();
var region = new CropRectangle(x: 50, y: 200, width: 600, height: 100);
input.LoadImage("form.png", region);

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

using IronOcr;
using IronSoftware.Drawing;

var ocr = new IronTesseract();

using var input = new OcrInput();
var region = new CropRectangle(x: 50, y: 200, width: 600, height: 100);
input.LoadImage("form.png", region);

OcrResult result = ocr.Read(input);
Console.WriteLine(result.Text);

Limiting recognition to a crop rectangle reduces processing time by up to 90 percent on large images. This technique is well-suited for invoice number extraction, form field reading, and ID document scanning. More details are available in the region OCR how-to guide.

How Do You Create a Searchable PDF from Recognised Text?

Converting scanned image archives into searchable PDF files is one of the highest-value OCR use cases. The resulting file preserves the original visual appearance while embedding an invisible text layer that PDF viewers, search engines, and screen readers can index.

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
input.Title = "Quarterly Report Q1 2026";
input.LoadImage("page1.png");
input.LoadImage("page2.png");
input.LoadImage("page3.png");

OcrResult result = ocr.Read(input);
result.SaveAsSearchablePdf("searchable-output.pdf");

Console.WriteLine("Searchable PDF created.");
Console.WriteLine($"Pages processed: {result.Pages.Count}");

using IronOcr;

var ocr = new IronTesseract();

using var input = new OcrInput();
input.Title = "Quarterly Report Q1 2026";
input.LoadImage("page1.png");
input.LoadImage("page2.png");
input.LoadImage("page3.png");

OcrResult result = ocr.Read(input);
result.SaveAsSearchablePdf("searchable-output.pdf");

Console.WriteLine("Searchable PDF created.");
Console.WriteLine($"Pages processed: {result.Pages.Count}");

How Do You Read Barcodes Alongside Text?

IronOCR can read barcodes and QR codes embedded in the same image as printed text, eliminating the need to run a separate barcode library. Enable the feature with one configuration property:

using IronOcr;

var ocr = new IronTesseract();
ocr.Configuration.ReadBarCodes = true;

using var input = new OcrInput();
input.LoadImage("shipping-label.png");

OcrResult result = ocr.Read(input);

Console.WriteLine("Text:");
Console.WriteLine(result.Text);

Console.WriteLine("Barcodes:");
foreach (var barcode in result.Barcodes)
{
    Console.WriteLine($"  {barcode.Format}: {barcode.Value}");
}

using IronOcr;

var ocr = new IronTesseract();
ocr.Configuration.ReadBarCodes = true;

using var input = new OcrInput();
input.LoadImage("shipping-label.png");

OcrResult result = ocr.Read(input);

Console.WriteLine("Text:");
Console.WriteLine(result.Text);

Console.WriteLine("Barcodes:");
foreach (var barcode in result.Barcodes)
{
    Console.WriteLine($"  {barcode.Format}: {barcode.Value}");
}

Supported barcode formats include Code 128, Code 39, EAN-13, EAN-8, UPC-A, UPC-E, PDF417, Data Matrix, and QR Code. Full details are in the IronOCR barcode reading guide.

This capability is particularly useful in logistics, healthcare, and retail applications where shipping labels, patient wristbands, and product tags carry both human-readable text and machine-readable barcodes.

How Do You Compare IronOCR with Other .NET OCR Options?

Developers evaluating OCR libraries for .NET typically consider IronOCR, Tesseract.NET, and cloud services such as Google Cloud Vision or Azure Computer Vision. The table below summarises the key differences:

Tesseract, maintained by Google as an open-source project, powers both IronOCR and Tesseract.NET under the hood. IronOCR adds .NET-idiomatic packaging, automatic model management, and the production output features (searchable PDF, hOCR export) that raw Tesseract bindings lack. Azure Computer Vision provides state-of-the-art cloud accuracy but introduces network latency and per-call costs that are unsuitable for high-volume or offline workflows.

For scenarios where data privacy regulations prohibit sending documents to external services -- healthcare records, legal documents, financial statements -- an on-premise library like IronOCR is the appropriate choice.

What Are Your Next Steps?

You now have the building blocks to add OCR to any .NET 10 application: installation via NuGet, basic image-to-text extraction, multi-page TIFF processing, language configuration, error handling, region-based reading, barcode detection, and searchable PDF generation.

To go deeper, explore these IronOCR resources:

• IronOCR documentation home -- full API reference and feature guides
• Image filter tutorial -- detailed guide to all preprocessing filters
• Barcode reading guide -- QR codes and linear barcodes alongside text
• Region OCR how-to -- crop-based recognition for forms and IDs
• Languages reference -- complete list of 125+ supported languages
• API reference -- all classes, methods, and properties

For licensing questions or to deploy IronOCR in a production environment, visit the IronOCR licensing page. A free trial license removes output watermarks during your evaluation period, and Iron Software's support team is available for technical questions at any tier.

Get stated with IronOCR now.

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