Message icon
フッターコンテンツにスキップ
  1. IronOCR
  2. IronOCRブログ
  3. IronOCRの使い方
  4. .NET OCR SDK
IRONOCRの使い方

IronOCRを使用して.NET OCR SDKを作成する方法

Kannaopat Udonpant
Kannapat Udonpant
公開日:

Suppose you’ve ever needed to extract text from scanned documents, PDFs, or images. In that case, you know how tricky it can be to handle different file formats, multiple languages, and low-quality scans. That’s where OCR (optical character recognition) comes in, turning scanned images and document files into editable text you can work with programmatically.

In this guide, we’ll explore how to build a high-performance .NET OCR SDK using IronOCR, showing you how to perform OCR, extract structured data, and generate searchable PDFs across multiple document types. You’ll learn how to process scanned PDFs, images, and other text files in a way that’s fast, reliable, and integrates seamlessly into .NET applications on desktop, web, or mobile devices.

What Makes IronOCR the Ideal .NET OCR SDK?

Building an OCR library from scratch requires months of development, image preprocessing, and extensive testing. IronOCR eliminates this overhead by providing a comprehensive .NET OCR SDK that supports various formats and integrates seamlessly into .NET applications.

The SDK handles the heavy lifting of text recognition while offering features typically found only in enterprise solutions:

  • High performance across various document formats and scanned images
  • Support for 125+ languages and handwritten text recognition
  • Adaptive binarization, font information, and bounding box support for zonal OCR
  • Ability to process scanned PDFs, image formats, and text blocks
  • Instant searchable document creation with hidden text layers

Unlike raw Tesseract implementations, IronOCR works immediately across Windows, Linux, macOS, and cloud platforms, supporting OCR APIs, AI-assisted recognition, and seamless integration without additional configuration.

Getting Started with IronOCR

Installation takes seconds through NuGet Package Manager. Run:

Install-Package IronOcr

For detailed installation instructions, refer to the IronOCR documentation. Once installed, extracting text from scanned documents becomes straightforward:

using IronOcr;
public class OcrService
{
    private readonly IronTesseract _ocr;
    public OcrService()
    {
        _ocr = new IronTesseract();
    }
    public string ExtractText(string imagePath)
    {
        using var input = new OcrInput();
        input.LoadImage(imagePath);
        var result = _ocr.Read(input);
        return result.Text;
    }
}
using IronOcr;
public class OcrService
{
    private readonly IronTesseract _ocr;
    public OcrService()
    {
        _ocr = new IronTesseract();
    }
    public string ExtractText(string imagePath)
    {
        using var input = new OcrInput();
        input.LoadImage(imagePath);
        var result = _ocr.Read(input);
        return result.Text;
    }
}
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

This code creates a reusable OCR service that handles various image formats, including JPEG, PNG, TIFF, and BMP, as well as PDF documents and other document formats, all automatically.

To test it, we'll run it through our main class with this example image:

class Program
{
    static void Main(string[] args)
    {
        var ocrService = new OcrService();
        string imagePath = "test.png"; // Replace with your image path
        string extractedText = ocrService.ExtractText(imagePath);
        Console.WriteLine(extractedText);
    }
}
class Program
{
    static void Main(string[] args)
    {
        var ocrService = new OcrService();
        string imagePath = "test.png"; // Replace with your image path
        string extractedText = ocrService.ExtractText(imagePath);
        Console.WriteLine(extractedText);
    }
}
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

Output

How to Create a .NET OCR SDK with IronOCR: Figure 2 - Example console output

Building Core OCR Functionality

Real-world applications need more than basic text extraction. IronOCR provides comprehensive document processing capabilities:

// Async document processing with barcodes
 public async Task<ProcessedDocument> ProcessDocumentAsync(string filePath)
 {
     using var input = new OcrInput();
     LoadFile(input, filePath);
     input.DeNoise();
     input.Deskew();
     var result = await _ocr.ReadAsync(input);
     return new ProcessedDocument
     {
         Text = result.Text,
         Confidence = result.Confidence,
         Barcodes = result.Barcodes.Select(b => b.Value).ToList()
     };
 }
// Helper to load image or PDF
private void LoadFile(OcrInput input, string filePath)
{
    if (filePath.EndsWith(".pdf", StringComparison.OrdinalIgnoreCase))
        input.LoadPdf(filePath);
    else
        input.LoadImage(filePath);
}
// Model for processed documents with barcodes
public class ProcessedDocument
{
    public string Text { get; set; }
    public double Confidence { get; set; }
    public List<string> Barcodes { get; set; }
}
// Async document processing with barcodes
 public async Task<ProcessedDocument> ProcessDocumentAsync(string filePath)
 {
     using var input = new OcrInput();
     LoadFile(input, filePath);
     input.DeNoise();
     input.Deskew();
     var result = await _ocr.ReadAsync(input);
     return new ProcessedDocument
     {
         Text = result.Text,
         Confidence = result.Confidence,
         Barcodes = result.Barcodes.Select(b => b.Value).ToList()
     };
 }
// Helper to load image or PDF
private void LoadFile(OcrInput input, string filePath)
{
    if (filePath.EndsWith(".pdf", StringComparison.OrdinalIgnoreCase))
        input.LoadPdf(filePath);
    else
        input.LoadImage(filePath);
}
// Model for processed documents with barcodes
public class ProcessedDocument
{
    public string Text { get; set; }
    public double Confidence { get; set; }
    public List<string> Barcodes { get; set; }
}
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

This implementation handles multiple documents, applies image preprocessing, and extracts barcodes and text from the same document. The async pattern ensures high performance in .NET applications.

Output

How to Create a .NET OCR SDK with IronOCR: Figure 3 - OCR input image vs. output text

Enhancing Accuracy with Built-in Features

IronOCR's preprocessing capabilities significantly improve recognition accuracy on real-world documents:

// OCR optimized for low-quality images
    public string ProcessLowQualityDocument(string filePath)
    {
        using var input = new OcrInput();
        LoadFile(input, filePath);
        // Preprocessing for low-quality documents
        input.DeNoise();
        input.Deskew();
        input.Scale(150);
        input.Binarize();
        input.EnhanceResolution(300);
        var result = _ocr.Read(input);
        return result.Text;
    }
// OCR optimized for low-quality images
    public string ProcessLowQualityDocument(string filePath)
    {
        using var input = new OcrInput();
        LoadFile(input, filePath);
        // Preprocessing for low-quality documents
        input.DeNoise();
        input.Deskew();
        input.Scale(150);
        input.Binarize();
        input.EnhanceResolution(300);
        var result = _ocr.Read(input);
        return result.Text;
    }
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

Each filter targets specific issues with document quality. DeNoise() removes artifacts from scanning, Deskew() corrects tilted pages, and EnhanceResolution() sharpens blurry text.

These filters work together to achieve accurate text extraction even from poor-quality sources. According to discussions on Stack Overflow, proper preprocessing can improve OCR accuracy by up to 40%.

Advanced Data Extraction SDK Capabilities

IronOCR extends beyond basic text extraction with features essential for modern .NET OCR SDK applications:

// Create a searchable PDF from an image or PDF
  public void CreateSearchablePdf(string inputPath, string outputPath)
  {
      using var input = new OcrInput();
      LoadFile(input, inputPath);
      _ocr.Read(input).SaveAsSearchablePdf(outputPath);
  }
  // Extract structured data (phone numbers, emails, amounts) from text
  public List<string> ExtractStructuredData(string filePath)
  {
      using var input = new OcrInput();
      LoadFile(input, filePath);
      var result = _ocr.Read(input);
      var text = result.Text;
      var phoneNumbers = Regex.Matches(text, @"\+?\d[\d\s\-]{7,}\d")
                              .Select(m => m.Value).ToList();
      var emails = Regex.Matches(text, @"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-z]{2,}")
                        .Select(m => m.Value).ToList();
      var amounts = Regex.Matches(text, @"\$\d+(?:\.\d{2})?")
                         .Select(m => m.Value).ToList();
      return phoneNumbers.Concat(emails).Concat(amounts).ToList();
  }
// Create a searchable PDF from an image or PDF
  public void CreateSearchablePdf(string inputPath, string outputPath)
  {
      using var input = new OcrInput();
      LoadFile(input, inputPath);
      _ocr.Read(input).SaveAsSearchablePdf(outputPath);
  }
  // Extract structured data (phone numbers, emails, amounts) from text
  public List<string> ExtractStructuredData(string filePath)
  {
      using var input = new OcrInput();
      LoadFile(input, filePath);
      var result = _ocr.Read(input);
      var text = result.Text;
      var phoneNumbers = Regex.Matches(text, @"\+?\d[\d\s\-]{7,}\d")
                              .Select(m => m.Value).ToList();
      var emails = Regex.Matches(text, @"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-z]{2,}")
                        .Select(m => m.Value).ToList();
      var amounts = Regex.Matches(text, @"\$\d+(?:\.\d{2})?")
                         .Select(m => m.Value).ToList();
      return phoneNumbers.Concat(emails).Concat(amounts).ToList();
  }
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

The code we've written here shows two key OCR operations. CreateSearchablePdf converts an input scanned PDF or image into a searchable document with editable text for easy text recognition across multiple document formats.

ExtractStructuredData processes the same scanned document to extract data, such as phone numbers, emails, and amounts, from diverse document types, enabling .NET applications to handle scanned images, text files, and PDF documents efficiently.

Production-Ready Implementation

Deploy IronOCR confidently with built-in production features:

public class ProductionOcrService
{
    private readonly IronTesseract _ocr;
    private readonly ILogger _logger;
    public ProductionOcrService(ILogger logger)
    {
        _logger = logger;
        _ocr = new IronTesseract();
        // Production configuration
        _ocr.Configuration.RenderSearchablePdfsAndHocr = true;
        _ocr.Configuration.ReadBarCodes = true;
    }
    public async Task<string> ProcessBatchAsync(string[] documents)
    {
        var results = new List<string>();
        // Parallel processing for performance
        await Parallel.ForEachAsync(documents, async (doc, ct) =>
        {
            try
            {
                var text = await ExtractTextAsync(doc);
                results.Add(text);
                _logger.LogInformation($"Processed: {doc}");
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, $"Failed: {doc}");
            }
        });
        return string.Join("\n", results);
    }
}
public class ProductionOcrService
{
    private readonly IronTesseract _ocr;
    private readonly ILogger _logger;
    public ProductionOcrService(ILogger logger)
    {
        _logger = logger;
        _ocr = new IronTesseract();
        // Production configuration
        _ocr.Configuration.RenderSearchablePdfsAndHocr = true;
        _ocr.Configuration.ReadBarCodes = true;
    }
    public async Task<string> ProcessBatchAsync(string[] documents)
    {
        var results = new List<string>();
        // Parallel processing for performance
        await Parallel.ForEachAsync(documents, async (doc, ct) =>
        {
            try
            {
                var text = await ExtractTextAsync(doc);
                results.Add(text);
                _logger.LogInformation($"Processed: {doc}");
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, $"Failed: {doc}");
            }
        });
        return string.Join("\n", results);
    }
}
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

This pattern demonstrates parallel processing for batch operations, structured logging for monitoring, and graceful error handling that prevents single-document failures from stopping entire batches.

Real-World Application: Invoice Processing

Here's how organizations use IronOCR as their .NET OCR SDK to automate invoice processing:

// Extract structured invoice data
    public Invoice ExtractInvoiceData(string invoicePath)
    {
        using var input = new OcrInput();
        LoadFile(input, invoicePath);
        // Preprocessing for documents
        input.DeNoise();
        input.Deskew();
        var result = _ocr.Read(input);
        var text = result.Text;
        return new Invoice
        {
            InvoiceNumber = ExtractInvoiceNumber(text),
            Date = ExtractDate(text),
            TotalAmount = ExtractAmount(text),
            RawText = text
        };
    }
    // --- Helper methods for invoice parsing ---
    private string ExtractInvoiceNumber(string text)
    {
        // Example: Invoice #: 12345
        var match = Regex.Match(text, @"Invoice\s*#?:?\s*(\S+)");
        return match.Success ? match.Groups[1].Value : null;
    }
    private DateOnly? ExtractDate(string text)
    {
        // Numeric dates
        var numericMatch = Regex.Match(text, @"\b(\d{1,2}/\d{1,2}/\d{2,4})\b");
        if (numericMatch.Success && DateTime.TryParse(numericMatch.Groups[1].Value, out var numericDate))
            return DateOnly.FromDateTime(numericDate);
        // Written-out dates
        var writtenMatch = Regex.Match(text,
            @"\b(January|February|March|April|May|June|July|August|September|October|November|December)\s+(\d{1,2}),?\s+(\d{4})\b",
            RegexOptions.IgnoreCase);
        if (writtenMatch.Success && DateTime.TryParse(writtenMatch.Value, out var writtenDate))
            return DateOnly.FromDateTime(writtenDate);
        return null;
    }
    private decimal? ExtractAmount(string text)
    {
        var match = Regex.Match(text, @"\$\s*(\d+(?:\.\d{2})?)");
        if (match.Success && decimal.TryParse(match.Groups[1].Value, out var amount))
            return amount;
        return null;
    }
// Extract structured invoice data
    public Invoice ExtractInvoiceData(string invoicePath)
    {
        using var input = new OcrInput();
        LoadFile(input, invoicePath);
        // Preprocessing for documents
        input.DeNoise();
        input.Deskew();
        var result = _ocr.Read(input);
        var text = result.Text;
        return new Invoice
        {
            InvoiceNumber = ExtractInvoiceNumber(text),
            Date = ExtractDate(text),
            TotalAmount = ExtractAmount(text),
            RawText = text
        };
    }
    // --- Helper methods for invoice parsing ---
    private string ExtractInvoiceNumber(string text)
    {
        // Example: Invoice #: 12345
        var match = Regex.Match(text, @"Invoice\s*#?:?\s*(\S+)");
        return match.Success ? match.Groups[1].Value : null;
    }
    private DateOnly? ExtractDate(string text)
    {
        // Numeric dates
        var numericMatch = Regex.Match(text, @"\b(\d{1,2}/\d{1,2}/\d{2,4})\b");
        if (numericMatch.Success && DateTime.TryParse(numericMatch.Groups[1].Value, out var numericDate))
            return DateOnly.FromDateTime(numericDate);
        // Written-out dates
        var writtenMatch = Regex.Match(text,
            @"\b(January|February|March|April|May|June|July|August|September|October|November|December)\s+(\d{1,2}),?\s+(\d{4})\b",
            RegexOptions.IgnoreCase);
        if (writtenMatch.Success && DateTime.TryParse(writtenMatch.Value, out var writtenDate))
            return DateOnly.FromDateTime(writtenDate);
        return null;
    }
    private decimal? ExtractAmount(string text)
    {
        var match = Regex.Match(text, @"\$\s*(\d+(?:\.\d{2})?)");
        if (match.Success && decimal.TryParse(match.Groups[1].Value, out var amount))
            return amount;
        return null;
    }
IRON VB CONVERTER ERROR developers@ironsoftware.com
$vbLabelText   $csharpLabel

This approach processes thousands of invoices daily, extracting key fields for automatic entry into accounting systems.

Output

How to Create a .NET OCR SDK with IronOCR: Figure 4 - Invoice OCR output

Conclusion

IronOCR transforms .NET applications into sophisticated document processing solutions without the complexity of building OCR from scratch. With extensive language support, superior accuracy, and production-ready features, it's the complete .NET OCR SDK that developers trust for enterprise applications.

IronOCR offers flexible licensing options starting at $liteLicense for single-developer use, with options scaling to enterprise deployments. The royalty-free model means no additional costs when distributing your OCR SDK applications to customers.

Ready to build your .NET OCR SDK? Start your free trial to begin building production applications today.

NuGet 購入の準備ができていませんか？

PM >  Install-Package IronOcr

IronOCR を NuGet でチェックしてください。1000万回以上のダウンロードで、C#によるPDF開発を変革しています。 DLL または Windowsインストーラー をダウンロードすることもできます。

よくある質問

IronOCRの.NET OCR SDKは、C#アプリケーションに光学文字認識機能を統合するために設計されたライブラリであり、開発者が画像、PDF、スキャンされたドキュメントからテキストを抽出できるようにします。

IronOCRの.NET SDKの主な特徴は何ですか？

IronOCRの.NET SDKは、シンプルなAPI、複数の言語のサポート、クロスプラットフォームの互換性、さまざまなファイル形式や低品質スキャンに対応するための高度な機能を提供します。

IronOCRの.NET SDKは、シンプルなAPI、複数の言語のサポート、クロスプラットフォームの互換性、およびさまざまなファイル形式や低品質のスキャンに対応する高度な機能を提供します。

IronOCRはどのように異なる言語を処理しますか？

IronOCRは低品質のスキャンを処理できますか？

はい、IronOCRは低品質のスキャンに効果的に対応するように設計されており、困難なシナリオであってもテキスト認識精度を向上させる高度なアルゴリズムを採用しています。

IronOCRの.NET SDKはクロスプラットフォームですか？

IronOCRの.NET SDKはクロスプラットフォームであり、さまざまなオペレーティングシステムで使用できるため、さまざまな開発環境にとって柔軟性があります。

IronOCRはどのようなファイル形式をサポートしていますか？

IronOCRは、画像、PDF、スキャンされたドキュメントなどの幅広いファイル形式をサポートし、異なるメディアでのテキスト認識タスクに柔軟性を提供します。

開発者はIronOCRをどのようにプロジェクトに統合できますか？

開発者はIronOCRのシンプルなAPIを使用して、C#プロジェクトに簡単に統合し、アプリケーションにOCR機能を追加するプロセスを簡素化できます。

IronOCRのユースケースにはどのようなものがありますか？

IronOCRは、ドキュメント管理システム、自動データ入力、コンテンツのデジタル化、画像やPDFからのテキスト抽出を必要とするあらゆるアプリケーションで利用できます。

このウェブページでは、IronOCRの.NET OCR SDKの概要を提供し、C#アプリケーション向けのテキスト認識機能において、シンプルなAPI、企業レベルのサポート、さまざまなドキュメント形式や言語を扱うためのクロスプラットフォーム機能などの機能に焦点を当てています。

Kannaopat Udonpant
Kannapat Udonpant
  今すぐエンジニアリングチームとチャット
ソフトウェアエンジニア
ソフトウェアエンジニアになる前に、Kannapatは北海道大学で環境資源の博士号を修了しました。博士号を追求する間に、彼はバイオプロダクションエンジニアリング学科の一部である車両ロボティクスラボラトリーのメンバーになりました。2022年には、C#のスキルを活用してIron Softwareのエンジニアリングチームに参加し、IronPDFに注力しています。Kannapatは、IronPDFの多くのコードを執筆している開発者から直接学んでいるため、この仕事を大切にしています。同僚から学びながら、Iron Softwareでの働く社会的側面も楽しんでいます。コードやドキュメントを書いていない時は、KannapatはPS5でゲームをしたり、『The Last of Us』を再視聴したりしていることが多いです。

関連する記事

30日間の無料体験 → 完全な製品。制限なし。クレジットカード不要。 無料トライアルを開始