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

How Do I Set Up an OCR Library in My .NET Project?

Setting up optical character recognition (OCR) in Visual Studio requires just a few steps. The IronOCR library is available via NuGet, making integration straightforward for any Windows application.

Open Visual Studio and create a new Console Application project. In the Solution Explorer, right-click on References and select "Manage NuGet Packages." Search for "IronOcr" and install the package. The NuGet package manager downloads all required DLL files and adds references to your project automatically.

// Install via Package Manager Console
Install-Package IronOCR

// Install via Package Manager Console
Install-Package IronOCR

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Once installed, add the using statement to import the IronOCR namespace into your program. The library supports .NET Framework 4.6.2+ and .NET Core, ensuring compatibility across different project types and Windows versions.

How Can I Extract Text from an Image File?

The first step in the OCR process is loading an image and passing it through the OCR engine. IronOCR provides the IronTesseract class as the primary OCR API for character recognition operations. This OCR sample demonstrates the fundamental approach to extracting text from any image file.

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        // Initialize the new Tesseract engine
        var ocr = new IronTesseract();
        // Load the image file and perform OCR
        using (var input = new OcrInput())
        {
            input.LoadImage(@"sample-document.png");
            // Process the image and extract text
            OcrResult result = ocr.Read(input);
            // Output the recognized text
            var text = result.Text;
            Console.WriteLine(text);
        }
    }
}

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        // Initialize the new Tesseract engine
        var ocr = new IronTesseract();
        // Load the image file and perform OCR
        using (var input = new OcrInput())
        {
            input.LoadImage(@"sample-document.png");
            // Process the image and extract text
            OcrResult result = ocr.Read(input);
            // Output the recognized text
            var text = result.Text;
            Console.WriteLine(text);
        }
    }
}

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How Do I Process Scanned Documents and TIFF Files?

Real-world applications often require processing multi-page scanned documents stored as TIFF files. The OCR library handles these scenarios efficiently by allowing developers to load specific page ranges or process entire documents. This sample code shows how to work with multi-frame TIFF images.

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        using (var input = new OcrInput())
        {
            // Load specific pages from a multi-page TIFF file
            int[] pageIndices = new int[] { 0, 1, 2 };
            input.LoadImageFrames(@"scanned-documents.tiff", pageIndices);
            // Apply image enhancement for better results
            input.Deskew();
            OcrResult result = ocr.Read(input);
            // Access page-by-page results
            foreach (var page in result.Pages)
            {
                Console.WriteLine($"Page {page.PageNumber}:");
                Console.WriteLine(page.Text);
            }
        }
    }
}

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        using (var input = new OcrInput())
        {
            // Load specific pages from a multi-page TIFF file
            int[] pageIndices = new int[] { 0, 1, 2 };
            input.LoadImageFrames(@"scanned-documents.tiff", pageIndices);
            // Apply image enhancement for better results
            input.Deskew();
            OcrResult result = ocr.Read(input);
            // Access page-by-page results
            foreach (var page in result.Pages)
            {
                Console.WriteLine($"Page {page.PageNumber}:");
                Console.WriteLine(page.Text);
            }
        }
    }
}

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How Can I Handle OCR Code Errors and Improve Recognition Results?

Production applications require proper error handling to manage various exception scenarios. Image quality issues, unsupported file formats, or corrupted files can cause the OCR process to fail. Implementing exception handling ensures your application responds gracefully to these situations.

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        // Configure the OCR engine for your language
        ocr.Language = OcrLanguage.English;
        try
        {
            using (var input = new OcrInput())
            {
                input.LoadImage(@"document.png");
                // Enhance low-quality images
                input.DeNoise();
                input.Deskew();
                OcrResult result = ocr.Read(input);
                if (result.Text.Length > 0)
                {
                    Console.WriteLine("Recognized text:");
                    Console.WriteLine(result.Text);
                }
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"OCR Error: {ex.Message}");
        }
    }
}

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        // Configure the OCR engine for your language
        ocr.Language = OcrLanguage.English;
        try
        {
            using (var input = new OcrInput())
            {
                input.LoadImage(@"document.png");
                // Enhance low-quality images
                input.DeNoise();
                input.Deskew();
                OcrResult result = ocr.Read(input);
                if (result.Text.Length > 0)
                {
                    Console.WriteLine("Recognized text:");
                    Console.WriteLine(result.Text);
                }
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"OCR Error: {ex.Message}");
        }
    }
}

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The Language property configures which language pack the OCR engine uses for text recognition. IronOCR supports over 125 languages, each available as separate NuGet packages. The DeNoise filter removes digital artifacts from scanned documents, while Deskew corrects alignment—both critical for achieving optimal recognition results from imperfect source images.

How Do I Create a Searchable PDF from Recognized Text?

Converting scanned documents into searchable PDF files represents one of the most valuable OCR applications. Users can then search, select, and copy text from previously image-only documents. This transformation enables document management systems to index content and improve accessibility.

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        using (var input = new OcrInput())
        {
            // Set document metadata
            input.Title = "Converted Document";
            // Load source images or existing PDF
            input.LoadImage(@"page1.png");
            input.LoadImage(@"page2.png");
            OcrResult result = ocr.Read(input);
            // Save as searchable PDF with embedded text layer
            result.SaveAsSearchablePdf(@"searchable-output.pdf");
            Console.WriteLine("Searchable PDF created successfully.");
            Console.WriteLine($"Total pages processed: {result.Pages.Count}");
        }
    }
}

using System;
using IronOcr;
class Program
{
    static void Main(string[] args)
    {
        var ocr = new IronTesseract();
        using (var input = new OcrInput())
        {
            // Set document metadata
            input.Title = "Converted Document";
            // Load source images or existing PDF
            input.LoadImage(@"page1.png");
            input.LoadImage(@"page2.png");
            OcrResult result = ocr.Read(input);
            // Save as searchable PDF with embedded text layer
            result.SaveAsSearchablePdf(@"searchable-output.pdf");
            Console.WriteLine("Searchable PDF created successfully.");
            Console.WriteLine($"Total pages processed: {result.Pages.Count}");
        }
    }
}

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Conclusion

Implementing optical character recognition in C# projects becomes straightforward with IronOCR. The library handles complex image processing, supports multiple image formats and languages, and provides flexible output options including searchable PDF generation. From simple text extraction to processing multi-page TIFF documents, the samples in this tutorial demonstrate the core workflows developers need.

The IronOCR documentation provides additional code examples for advanced image filters, barcode reading, and region-specific OCR processing. The API reference details all available classes and methods for building comprehensive document processing solutions.

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