C# OCR Image to Text Tutorial: Convert Images to Text Without Tesseract

How Do I Read Text from Images in .NET Applications?

To achieve C# OCR image to text functionality in your .NET applications, you'll need a reliable OCR library. IronOCR provides a managed solution using the IronOcr.IronTesseract class that maximizes both accuracy and speed without requiring external dependencies.

First, install IronOCR into your Visual Studio project. You can download the IronOCR DLL directly or use NuGet Package Manager.

Install-Package IronOcr

Why Choose IronOCR for C# OCR Without Tesseract?

When you need to convert images to text in C#, IronOCR offers significant advantages over traditional Tesseract implementations:

• Works immediately in pure .NET environments
• No Tesseract installation or configuration required
• Runs the latest engines: Tesseract 5 (plus Tesseract 4 & 3)
• Compatible with .NET Framework 4.5+, .NET Standard 2+, and .NET Core 2, 3, 5, 6, 7, 8, 9, and 10
• Improves accuracy and speed compared to vanilla Tesseract
• Supports Xamarin, Mono, Azure, and Docker deployments
• Manages complex Tesseract dictionaries through NuGet packages
• Handles PDFs, MultiFrame TIFFs, and all major image formats automatically
• Corrects low-quality and skewed scans for optimal results

How to Use IronOCR C# Tutorial for Basic OCR?

This Iron Tesseract C# example demonstrates the simplest way to read text from image using IronOCR. The IronOcr.IronTesseract class extracts text and returns it as a string.

// Basic C# OCR image to text conversion using IronOCR
// This example shows how to extract text from images without complex setup

using IronOcr;
using System;

try
{
    // Initialize IronTesseract for OCR operations
    var ocrEngine = new IronTesseract();

    // Path to your image file - supports PNG, JPG, TIFF, BMP, and more
    var imagePath = @"img\Screenshot.png";

    // Create input and perform OCR to convert image to text
    using (var input = new OcrInput(imagePath))
    {
        // Read text from image and get results
        OcrResult result = ocrEngine.Read(input);

        // Display extracted text
        Console.WriteLine(result.Text);
    }
}
catch (OcrException ex)
{
    // Handle OCR-specific errors
    Console.WriteLine($"OCR Error: {ex.Message}");
}
catch (Exception ex)
{
    // Handle general errors
    Console.WriteLine($"Error: {ex.Message}");
}

// Basic C# OCR image to text conversion using IronOCR
// This example shows how to extract text from images without complex setup

using IronOcr;
using System;

try
{
    // Initialize IronTesseract for OCR operations
    var ocrEngine = new IronTesseract();

    // Path to your image file - supports PNG, JPG, TIFF, BMP, and more
    var imagePath = @"img\Screenshot.png";

    // Create input and perform OCR to convert image to text
    using (var input = new OcrInput(imagePath))
    {
        // Read text from image and get results
        OcrResult result = ocrEngine.Read(input);

        // Display extracted text
        Console.WriteLine(result.Text);
    }
}
catch (OcrException ex)
{
    // Handle OCR-specific errors
    Console.WriteLine($"OCR Error: {ex.Message}");
}
catch (Exception ex)
{
    // Handle general errors
    Console.WriteLine($"Error: {ex.Message}");
}

This code achieves 100% accuracy on clear images, extracting text exactly as it appears:

IronOCR Simple Example

In this simple example we test the accuracy of our C# OCR library to read text from a PNG Image. This is a very basic test, but things will get more complicated as the tutorial continues.

The quick brown fox jumps over the lazy dog

The IronTesseract class handles complex OCR operations internally. It automatically scans for alignment, optimizes resolution, and uses AI to read text from image using IronOCR with human-level accuracy.

Despite the sophisticated processing happening behind the scenes - including image analysis, engine optimization, and intelligent text recognition - the OCR process matches human reading speed while maintaining exceptional accuracy levels.

Screenshot demonstrating IronOCR's ability to extract text from a PNG image with perfect accuracy

How to Implement Advanced C# OCR Without Tesseract Configuration?

For production applications requiring optimal performance when you convert images to text in C#, use the OcrInput and IronTesseract classes together. This approach provides fine-grained control over the OCR process.

How to Get Started with OcrInput and IronTesseract?

Here's a recommended configuration for this IronOCR C# tutorial that works well with most document types:

using IronOcr;

// Initialize IronTesseract for advanced OCR operations
IronTesseract ocr = new IronTesseract();

// Create input container for processing multiple images
using (OcrInput input = new OcrInput())
{
    // Process specific pages from multi-page TIFF files
    int[] pageIndices = new int[] { 1, 2 };

    // Load TIFF frames - perfect for scanned documents
    input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

    // Execute OCR to read text from image using IronOCR
    OcrResult result = ocr.Read(input);

    // Output the extracted text
    Console.WriteLine(result.Text);
}

using IronOcr;

// Initialize IronTesseract for advanced OCR operations
IronTesseract ocr = new IronTesseract();

// Create input container for processing multiple images
using (OcrInput input = new OcrInput())
{
    // Process specific pages from multi-page TIFF files
    int[] pageIndices = new int[] { 1, 2 };

    // Load TIFF frames - perfect for scanned documents
    input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

    // Execute OCR to read text from image using IronOCR
    OcrResult result = ocr.Read(input);

    // Output the extracted text
    Console.WriteLine(result.Text);
}

$vbLabelText   $csharpLabel

This configuration consistently achieves near-perfect accuracy on medium-quality scans. The LoadImageFrames method efficiently handles multi-page documents, making it ideal for batch processing scenarios.

Sample TIFF document demonstrating IronOCR's multi-page text extraction capabilities

The ability to read text from images and barcodes in scanned documents like TIFFs showcases how IronOCR simplifies complex OCR tasks. The library excels with real-world documents, seamlessly handling multi-page TIFFs and PDF text extraction.

How Does IronOCR Handle Low-Quality Scans?

Low-resolution document with noise that IronOCR can process accurately using image filters

When working with imperfect scans containing distortion and digital noise, IronOCR outperforms other C# OCR libraries. It's specifically designed for real-world scenarios rather than pristine test images.

// Advanced Iron Tesseract C# example for low-quality images
using IronOcr;
using System;

var ocr = new IronTesseract();

try
{
    using (var input = new OcrInput())
    {
        // Load specific pages from poor-quality TIFF
        var pageIndices = new int[] { 0, 1 };
        input.LoadImageFrames(@"img\Potter.LowQuality.tiff", pageIndices);

        // Apply deskew filter to correct rotation and perspective
        input.Deskew(); // Critical for improving accuracy on skewed scans

        // Perform OCR with enhanced preprocessing
        OcrResult result = ocr.Read(input);

        // Display results
        Console.WriteLine("Recognized Text:");
        Console.WriteLine(result.Text);
    }
}
catch (Exception ex)
{
    Console.WriteLine($"Error during OCR: {ex.Message}");
}

// Advanced Iron Tesseract C# example for low-quality images
using IronOcr;
using System;

var ocr = new IronTesseract();

try
{
    using (var input = new OcrInput())
    {
        // Load specific pages from poor-quality TIFF
        var pageIndices = new int[] { 0, 1 };
        input.LoadImageFrames(@"img\Potter.LowQuality.tiff", pageIndices);

        // Apply deskew filter to correct rotation and perspective
        input.Deskew(); // Critical for improving accuracy on skewed scans

        // Perform OCR with enhanced preprocessing
        OcrResult result = ocr.Read(input);

        // Display results
        Console.WriteLine("Recognized Text:");
        Console.WriteLine(result.Text);
    }
}
catch (Exception ex)
{
    Console.WriteLine($"Error during OCR: {ex.Message}");
}

$vbLabelText   $csharpLabel

Using Input.Deskew(), accuracy improves to 99.8% on low-quality scans, nearly matching high-quality results. This demonstrates why IronOCR is the preferred choice for C# OCR without Tesseract complications.

Image filters may slightly increase processing time but significantly reduce overall OCR duration. Finding the right balance depends on your document quality.

For most scenarios, Input.Deskew() and Input.DeNoise() provide reliable improvements to OCR performance. Learn more about image preprocessing techniques.

How to Optimize OCR Performance and Speed?

The most significant factor affecting OCR speed when you convert images to text in C# is input quality. Higher DPI (~200 dpi) with minimal noise produces the fastest and most accurate results.

While IronOCR excels at correcting imperfect documents, this enhancement requires additional processing time.

Choose image formats with minimal compression artifacts. TIFF and PNG typically yield faster results than JPEG due to lower digital noise.

using IronOcr;

// Configure for speed - ideal for clean documents
IronTesseract ocr = new IronTesseract();

// Exclude problematic characters to speed up recognition
ocr.Configuration.BlackListCharacters = "~`$#^*_{[]}|\\";

// Use automatic page segmentation
ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.Auto;

// Select fast English language pack
ocr.Language = OcrLanguage.EnglishFast;

using (OcrInput input = new OcrInput())
{
    // Load specific pages from document
    int[] pageIndices = new int[] { 1, 2 };
    input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

    // Read with optimized settings
    OcrResult result = ocr.Read(input);
    Console.WriteLine(result.Text);
}

using IronOcr;

// Configure for speed - ideal for clean documents
IronTesseract ocr = new IronTesseract();

// Exclude problematic characters to speed up recognition
ocr.Configuration.BlackListCharacters = "~`$#^*_{[]}|\\";

// Use automatic page segmentation
ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.Auto;

// Select fast English language pack
ocr.Language = OcrLanguage.EnglishFast;

using (OcrInput input = new OcrInput())
{
    // Load specific pages from document
    int[] pageIndices = new int[] { 1, 2 };
    input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

    // Read with optimized settings
    OcrResult result = ocr.Read(input);
    Console.WriteLine(result.Text);
}

How to Read Specific Areas of Images Using C# OCR?

The Iron Tesseract C# example below shows how to target specific regions using System.Drawing.Rectangle. This technique is invaluable for processing standardized forms where text appears in predictable locations.

using IronOcr;
using IronSoftware.Drawing;

// Initialize OCR engine for targeted region processing
var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Define exact region for OCR - coordinates in pixels
    var contentArea = new System.Drawing.Rectangle(
        x: 215, 
        y: 1250, 
        width: 1335, 
        height: 280
    );

    // Load image with specific area - perfect for forms and invoices
    input.AddImage("img/ComSci.png", contentArea);

    // Process only the defined region
    OcrResult result = ocr.Read(input);
    Console.WriteLine(result.Text);
}

using IronOcr;
using IronSoftware.Drawing;

// Initialize OCR engine for targeted region processing
var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Define exact region for OCR - coordinates in pixels
    var contentArea = new System.Drawing.Rectangle(
        x: 215, 
        y: 1250, 
        width: 1335, 
        height: 280
    );

    // Load image with specific area - perfect for forms and invoices
    input.AddImage("img/ComSci.png", contentArea);

    // Process only the defined region
    OcrResult result = ocr.Read(input);
    Console.WriteLine(result.Text);
}

How Many Languages Does IronOCR Support?

IronOCR provides 125 international languages through convenient language packs. Download them as DLLs from our website or via NuGet Package Manager.

Install language packs through the NuGet interface (search "IronOcr.Languages") or visit the complete language pack listing.

Supported languages include Arabic, Chinese (Simplified/Traditional), Japanese, Korean, Hindi, Russian, German, French, Spanish, and 115+ others, each optimized for accurate text recognition.

How to Implement OCR in Multiple Languages?

This IronOCR C# tutorial example demonstrates Arabic text recognition:

Install-Package IronOcr.Languages.Arabic

IronOCR accurately extracting Arabic text from a GIF image

// Install-Package IronOcr.Languages.Arabic
using IronOcr;

// Configure for Arabic language OCR
var ocr = new IronTesseract();
ocr.Language = OcrLanguage.Arabic;

using (var input = new OcrInput())
{
    // Load Arabic text image
    input.AddImage("img/arabic.gif");

    // IronOCR handles low-quality Arabic text that standard Tesseract cannot
    var result = ocr.Read(input);

    // Save to file (console may not display Arabic correctly)
    result.SaveAsTextFile("arabic.txt");
}

// Install-Package IronOcr.Languages.Arabic
using IronOcr;

// Configure for Arabic language OCR
var ocr = new IronTesseract();
ocr.Language = OcrLanguage.Arabic;

using (var input = new OcrInput())
{
    // Load Arabic text image
    input.AddImage("img/arabic.gif");

    // IronOCR handles low-quality Arabic text that standard Tesseract cannot
    var result = ocr.Read(input);

    // Save to file (console may not display Arabic correctly)
    result.SaveAsTextFile("arabic.txt");
}

$vbLabelText   $csharpLabel

Install-Package IronOcr.Languages.ChineseSimplified

// Multi-language OCR configuration
using IronOcr;

var ocr = new IronTesseract();

// Set primary language
ocr.Language = OcrLanguage.ChineseSimplified;

// Add secondary languages as needed
ocr.AddSecondaryLanguage(OcrLanguage.English);

// Custom .traineddata files can be added for specialized recognition
// ocr.AddSecondaryLanguage("path/to/custom.traineddata");

using (var input = new OcrInput())
{
    // Process multi-language document
    input.AddImage("img/MultiLanguage.jpeg");

    var result = ocr.Read(input);
    result.SaveAsTextFile("MultiLanguage.txt");
}

// Multi-language OCR configuration
using IronOcr;

var ocr = new IronTesseract();

// Set primary language
ocr.Language = OcrLanguage.ChineseSimplified;

// Add secondary languages as needed
ocr.AddSecondaryLanguage(OcrLanguage.English);

// Custom .traineddata files can be added for specialized recognition
// ocr.AddSecondaryLanguage("path/to/custom.traineddata");

using (var input = new OcrInput())
{
    // Process multi-language document
    input.AddImage("img/MultiLanguage.jpeg");

    var result = ocr.Read(input);
    result.SaveAsTextFile("MultiLanguage.txt");
}

How to Process Multi-Page Documents with C# OCR?

IronOCR seamlessly combines multiple pages or images into a single OcrResult. This feature enables powerful capabilities like creating searchable PDFs and extracting text from entire document sets.

Mix and match various sources - images, TIFF frames, and PDF pages - in a single OCR operation:

// Multi-source document processing
using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Add various image formats
    input.AddImage("image1.jpeg");
    input.AddImage("image2.png");

    // Process specific frames from multi-frame images
    int[] frameNumbers = { 1, 2 };
    input.AddImageFrames("image3.gif", frameNumbers);

    // Process all sources together
    OcrResult result = ocr.Read(input);

    // Verify page count
    Console.WriteLine($"{result.Pages.Count} Pages processed.");
}

// Multi-source document processing
using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Add various image formats
    input.AddImage("image1.jpeg");
    input.AddImage("image2.png");

    // Process specific frames from multi-frame images
    int[] frameNumbers = { 1, 2 };
    input.AddImageFrames("image3.gif", frameNumbers);

    // Process all sources together
    OcrResult result = ocr.Read(input);

    // Verify page count
    Console.WriteLine($"{result.Pages.Count} Pages processed.");
}

Process all pages of a TIFF file efficiently:

using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Define pages to process (0-based indexing)
    int[] pageIndices = new int[] { 0, 1 };

    // Load specific TIFF frames
    input.LoadImageFrames("MultiFrame.Tiff", pageIndices);

    // Extract text from all frames
    OcrResult result = ocr.Read(input);

    Console.WriteLine(result.Text);
    Console.WriteLine($"{result.Pages.Count} Pages processed");
}

using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Define pages to process (0-based indexing)
    int[] pageIndices = new int[] { 0, 1 };

    // Load specific TIFF frames
    input.LoadImageFrames("MultiFrame.Tiff", pageIndices);

    // Extract text from all frames
    OcrResult result = ocr.Read(input);

    Console.WriteLine(result.Text);
    Console.WriteLine($"{result.Pages.Count} Pages processed");
}

Convert TIFFs or PDFs to searchable formats:

using System;
using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Set document metadata
    input.Title = "Quarterly Report";

    // Combine multiple sources
    input.AddImage("image1.jpeg");
    input.AddImage("image2.png");

    // Add specific frames from animated images
    int[] gifFrames = new int[] { 1, 2 };
    input.AddImageFrames("image3.gif", gifFrames);

    // Create searchable PDF
    OcrResult result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

using System;
using IronOcr;

IronTesseract ocr = new IronTesseract();

using (OcrInput input = new OcrInput())
{
    // Set document metadata
    input.Title = "Quarterly Report";

    // Combine multiple sources
    input.AddImage("image1.jpeg");
    input.AddImage("image2.png");

    // Add specific frames from animated images
    int[] gifFrames = new int[] { 1, 2 };
    input.AddImageFrames("image3.gif", gifFrames);

    // Create searchable PDF
    OcrResult result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

Convert existing PDFs to searchable versions:

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Set PDF metadata
    input.Title = "Annual Report 2024";

    // Process existing PDF
    input.LoadPdf("example.pdf", "password");

    // Generate searchable version
    var result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Set PDF metadata
    input.Title = "Annual Report 2024";

    // Process existing PDF
    input.LoadPdf("example.pdf", "password");

    // Generate searchable version
    var result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

Apply the same technique to TIFF conversions:

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Configure document properties
    input.Title = "Scanned Archive Document";

    // Select pages to process
    var pageIndices = new int[] { 1, 2 };
    input.LoadImageFrames("example.tiff", pageIndices);

    // Create searchable PDF from TIFF
    OcrResult result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Configure document properties
    input.Title = "Scanned Archive Document";

    // Select pages to process
    var pageIndices = new int[] { 1, 2 };
    input.LoadImageFrames("example.tiff", pageIndices);

    // Create searchable PDF from TIFF
    OcrResult result = ocr.Read(input);
    result.SaveAsSearchablePdf("searchable.pdf");
}

How to Export OCR Results as HOCR HTML?

IronOCR supports HOCR HTML export, enabling structured PDF to HTML and TIFF to HTML conversions while preserving layout information:

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Set HTML title
    input.Title = "Document Archive";

    // Process multiple document types
    input.AddImage("image2.jpeg");
    input.AddPdf("example.pdf", "password");

    // Add TIFF pages
    var pageIndices = new int[] { 1, 2 };
    input.AddTiff("example.tiff", pageIndices);

    // Export as HOCR with position data
    OcrResult result = ocr.Read(input);
    result.SaveAsHocrFile("hocr.html");
}

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    // Set HTML title
    input.Title = "Document Archive";

    // Process multiple document types
    input.AddImage("image2.jpeg");
    input.AddPdf("example.pdf", "password");

    // Add TIFF pages
    var pageIndices = new int[] { 1, 2 };
    input.AddTiff("example.tiff", pageIndices);

    // Export as HOCR with position data
    OcrResult result = ocr.Read(input);
    result.SaveAsHocrFile("hocr.html");
}

Can IronOCR Read Barcodes Along with Text?

IronOCR uniquely combines text recognition with barcode reading capabilities, eliminating the need for separate libraries:

// Enable combined text and barcode recognition
using IronOcr;

var ocr = new IronTesseract();

// Enable barcode detection
ocr.Configuration.ReadBarCodes = true;

using (var input = new OcrInput())
{
    // Load image containing both text and barcodes
    input.AddImage("img/Barcode.png");

    // Process both text and barcodes
    var result = ocr.Read(input);

    // Extract barcode data
    foreach (var barcode in result.Barcodes)
    {
        Console.WriteLine($"Barcode Value: {barcode.Value}");
        Console.WriteLine($"Type: {barcode.Type}, Location: {barcode.Location}");
    }
}

// Enable combined text and barcode recognition
using IronOcr;

var ocr = new IronTesseract();

// Enable barcode detection
ocr.Configuration.ReadBarCodes = true;

using (var input = new OcrInput())
{
    // Load image containing both text and barcodes
    input.AddImage("img/Barcode.png");

    // Process both text and barcodes
    var result = ocr.Read(input);

    // Extract barcode data
    foreach (var barcode in result.Barcodes)
    {
        Console.WriteLine($"Barcode Value: {barcode.Value}");
        Console.WriteLine($"Type: {barcode.Type}, Location: {barcode.Location}");
    }
}

How to Access Detailed OCR Results and Metadata?

The IronOCR results object provides comprehensive data that advanced developers can leverage for sophisticated applications.

Each OcrResult contains hierarchical collections: pages, paragraphs, lines, words, and characters. All elements include detailed metadata like location, font information, and confidence scores.

Individual elements (paragraphs, words, barcodes) can be exported as images or bitmaps for further processing:

using System;
using IronOcr;
using IronSoftware.Drawing;

// Configure with barcode support
IronTesseract ocr = new IronTesseract
{
    Configuration = { ReadBarCodes = true }
};

using OcrInput input = new OcrInput();

// Process multi-page document
int[] pageIndices = { 1, 2 };
input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

OcrResult result = ocr.Read(input);

// Navigate the complete results hierarchy
foreach (var page in result.Pages)
{
    // Page-level data
    int pageNumber = page.PageNumber;
    string pageText = page.Text;
    int pageWordCount = page.WordCount;

    // Extract page elements
    OcrResult.Barcode[] barcodes = page.Barcodes;
    AnyBitmap pageImage = page.ToBitmap();
    double pageWidth = page.Width;
    double pageHeight = page.Height;

    foreach (var paragraph in page.Paragraphs)
    {
        // Paragraph properties
        int paragraphNumber = paragraph.ParagraphNumber;
        string paragraphText = paragraph.Text;
        double paragraphConfidence = paragraph.Confidence;
        var textDirection = paragraph.TextDirection;

        foreach (var line in paragraph.Lines)
        {
            // Line details including baseline information
            string lineText = line.Text;
            double lineConfidence = line.Confidence;
            double baselineAngle = line.BaselineAngle;
            double baselineOffset = line.BaselineOffset;

            foreach (var word in line.Words)
            {
                // Word-level data
                string wordText = word.Text;
                double wordConfidence = word.Confidence;

                // Font information (when available)
                if (word.Font != null)
                {
                    string fontName = word.Font.FontName;
                    double fontSize = word.Font.FontSize;
                    bool isBold = word.Font.IsBold;
                    bool isItalic = word.Font.IsItalic;
                }

                foreach (var character in word.Characters)
                {
                    // Character-level analysis
                    string charText = character.Text;
                    double charConfidence = character.Confidence;

                    // Alternative character choices for spell-checking
                    OcrResult.Choice[] alternatives = character.Choices;
                }
            }
        }
    }
}

using System;
using IronOcr;
using IronSoftware.Drawing;

// Configure with barcode support
IronTesseract ocr = new IronTesseract
{
    Configuration = { ReadBarCodes = true }
};

using OcrInput input = new OcrInput();

// Process multi-page document
int[] pageIndices = { 1, 2 };
input.LoadImageFrames(@"img\Potter.tiff", pageIndices);

OcrResult result = ocr.Read(input);

// Navigate the complete results hierarchy
foreach (var page in result.Pages)
{
    // Page-level data
    int pageNumber = page.PageNumber;
    string pageText = page.Text;
    int pageWordCount = page.WordCount;

    // Extract page elements
    OcrResult.Barcode[] barcodes = page.Barcodes;
    AnyBitmap pageImage = page.ToBitmap();
    double pageWidth = page.Width;
    double pageHeight = page.Height;

    foreach (var paragraph in page.Paragraphs)
    {
        // Paragraph properties
        int paragraphNumber = paragraph.ParagraphNumber;
        string paragraphText = paragraph.Text;
        double paragraphConfidence = paragraph.Confidence;
        var textDirection = paragraph.TextDirection;

        foreach (var line in paragraph.Lines)
        {
            // Line details including baseline information
            string lineText = line.Text;
            double lineConfidence = line.Confidence;
            double baselineAngle = line.BaselineAngle;
            double baselineOffset = line.BaselineOffset;

            foreach (var word in line.Words)
            {
                // Word-level data
                string wordText = word.Text;
                double wordConfidence = word.Confidence;

                // Font information (when available)
                if (word.Font != null)
                {
                    string fontName = word.Font.FontName;
                    double fontSize = word.Font.FontSize;
                    bool isBold = word.Font.IsBold;
                    bool isItalic = word.Font.IsItalic;
                }

                foreach (var character in word.Characters)
                {
                    // Character-level analysis
                    string charText = character.Text;
                    double charConfidence = character.Confidence;

                    // Alternative character choices for spell-checking
                    OcrResult.Choice[] alternatives = character.Choices;
                }
            }
        }
    }
}

Summary

IronOCR provides C# developers with the most advanced Tesseract API implementation, running seamlessly across Windows, Linux, and Mac platforms. Its ability to accurately read text from image using IronOCR - even from imperfect documents - sets it apart from basic OCR solutions.

The library's unique features include integrated barcode reading and the ability to export results as searchable PDFs or HOCR HTML, capabilities unavailable in standard Tesseract implementations.