Windows OCR Engine vs Tesseract: A Detailed Comparison

In today's digital age, Optical Character Recognition (OCR) technology has become integral to various industries, enabling the conversion of images and scanned documents into editable and searchable text.

Among the many OCR software available, such as Google Cloud Vision (Cloud Vision API), Adobe Acrobat Pro DC, ABBYY Finereader and so many more, Windows OCR Engine vs Tesseract, and IronOCR stand out as prominent contenders, each offering unique features and capabilities to aid document analysis.

This article aims to provide a comprehensive comparative analysis of these three OCR engines, evaluating their accuracy, performance, and ease of integration.

1. Introduction to OCR Engines

OCR engines are software tools designed to recognize and extract plain text from images, PDFs, and other scanned documents. They employ sophisticated algorithms and machine learning techniques to accurately identify characters and convert them into a machine-readable text file. Windows OCR Engine, Tesseract, and IronOCR represent three widely used OCR solutions, each with its strengths and applications.

2. Windows OCR Engine

The Windows OCR Engine, integrated into the Windows operating system, offers a convenient and user-friendly solution for extracting text from input images and scanned documents. Leveraging advanced image processing techniques, it can accurately recognize text in various languages and font styles. The Windows OCR Engine is accessible through the Windows Runtime API, enabling seamless integration into Windows applications with the capabilities of a command line tool.

2.1 Key Features of Windows OCR Engine

• Language Support: The Windows OCR Engine supports many languages, making it suitable for multilingual documents.
• Image Processing: It employs sophisticated image processing algorithms to enhance printed text recognition accuracy, even in low-quality images.
• Integration with Windows Applications: The Windows OCR Engine seamlessly integrates with Windows applications, allowing developers to fully incorporate OCR capabilities into their software.

2.2 Code Example

using System;
using System.IO;
using System.Text;
using System.Threading.Tasks;
class Program
{
    static async Task Main(string [] args)
    {
        // Provide the path to the image file
        string imagePath = "sample.png";
        try
        {
            // Instantiate the program class
            Program program = new Program();
            // Call the ExtractText method to extract text from the image
            string extractedText = await program.ExtractText(imagePath);
            // Display the extracted text
            Console.WriteLine("Extracted Text:");
            Console.WriteLine(extractedText);
        }
        catch (Exception ex)
        {
            Console.WriteLine("An error occurred: " + ex.Message);
        }
    }
    public async Task<string> ExtractText(string image)
    {
        // Initialize StringBuilder to store extracted text
        StringBuilder text = new StringBuilder();
        try
        {
            // Open the image file stream
            using (var fileStream = System.IO.File.OpenRead(image))
            {
                Console.WriteLine("Extracted Text:");
                // Create a BitmapDecoder from the image file stream
                var bmpDecoder = await Windows.Graphics.Imaging.BitmapDecoder.CreateAsync(fileStream.AsRandomAccessStream());
                // Get the software bitmap from the decoder
                var softwareBmp = await bmpDecoder.GetSoftwareBitmapAsync();
                // Create an OCR engine from user profile languages
                var ocrEngine = Windows.Media.Ocr.OcrEngine.TryCreateFromUserProfileLanguages();
                // Recognize text from the software bitmap
                var ocrResult = await ocrEngine.RecognizeAsync(softwareBmp);
                // Append each line of recognized text to the StringBuilder
                foreach (var line in ocrResult.Lines)
                {
                    text.AppendLine(line.Text);
                }
            }
        }
        catch (Exception ex)
        {
            throw ex; // Propagate the exception
        }
        // Return the extracted text
        return text.ToString();
    }
}

using System;
using System.IO;
using System.Text;
using System.Threading.Tasks;
class Program
{
    static async Task Main(string [] args)
    {
        // Provide the path to the image file
        string imagePath = "sample.png";
        try
        {
            // Instantiate the program class
            Program program = new Program();
            // Call the ExtractText method to extract text from the image
            string extractedText = await program.ExtractText(imagePath);
            // Display the extracted text
            Console.WriteLine("Extracted Text:");
            Console.WriteLine(extractedText);
        }
        catch (Exception ex)
        {
            Console.WriteLine("An error occurred: " + ex.Message);
        }
    }
    public async Task<string> ExtractText(string image)
    {
        // Initialize StringBuilder to store extracted text
        StringBuilder text = new StringBuilder();
        try
        {
            // Open the image file stream
            using (var fileStream = System.IO.File.OpenRead(image))
            {
                Console.WriteLine("Extracted Text:");
                // Create a BitmapDecoder from the image file stream
                var bmpDecoder = await Windows.Graphics.Imaging.BitmapDecoder.CreateAsync(fileStream.AsRandomAccessStream());
                // Get the software bitmap from the decoder
                var softwareBmp = await bmpDecoder.GetSoftwareBitmapAsync();
                // Create an OCR engine from user profile languages
                var ocrEngine = Windows.Media.Ocr.OcrEngine.TryCreateFromUserProfileLanguages();
                // Recognize text from the software bitmap
                var ocrResult = await ocrEngine.RecognizeAsync(softwareBmp);
                // Append each line of recognized text to the StringBuilder
                foreach (var line in ocrResult.Lines)
                {
                    text.AppendLine(line.Text);
                }
            }
        }
        catch (Exception ex)
        {
            throw ex; // Propagate the exception
        }
        // Return the extracted text
        return text.ToString();
    }
}

Imports System
Imports System.IO
Imports System.Text
Imports System.Threading.Tasks
Friend Class Program
	Shared Async Function Main(ByVal args() As String) As Task
		' Provide the path to the image file
		Dim imagePath As String = "sample.png"
		Try
			' Instantiate the program class
			Dim program As New Program()
			' Call the ExtractText method to extract text from the image
			Dim extractedText As String = Await program.ExtractText(imagePath)
			' Display the extracted text
			Console.WriteLine("Extracted Text:")
			Console.WriteLine(extractedText)
		Catch ex As Exception
			Console.WriteLine("An error occurred: " & ex.Message)
		End Try
	End Function
	Public Async Function ExtractText(ByVal image As String) As Task(Of String)
		' Initialize StringBuilder to store extracted text
		Dim text As New StringBuilder()
		Try
			' Open the image file stream
			Using fileStream = System.IO.File.OpenRead(image)
				Console.WriteLine("Extracted Text:")
				' Create a BitmapDecoder from the image file stream
				Dim bmpDecoder = Await Windows.Graphics.Imaging.BitmapDecoder.CreateAsync(fileStream.AsRandomAccessStream())
				' Get the software bitmap from the decoder
				Dim softwareBmp = Await bmpDecoder.GetSoftwareBitmapAsync()
				' Create an OCR engine from user profile languages
				Dim ocrEngine = Windows.Media.Ocr.OcrEngine.TryCreateFromUserProfileLanguages()
				' Recognize text from the software bitmap
				Dim ocrResult = Await ocrEngine.RecognizeAsync(softwareBmp)
				' Append each line of recognized text to the StringBuilder
				For Each line In ocrResult.Lines
					text.AppendLine(line.Text)
				Next line
			End Using
		Catch ex As Exception
			Throw ex ' Propagate the exception
		End Try
		' Return the extracted text
		Return text.ToString()
	End Function
End Class

2.2.1 Output

3. Tesseract

Tesseract, an open-source OCR engine developed by Google, has gained widespread popularity for its accuracy and versatility. It supports over 100 languages and can process various image formats, including TIFF, JPEG, and PNG. Tesseract OCR Engine employs deep learning algorithms and neural networks to achieve high levels of text recognition accuracy, making it suitable for a wide range of applications.

3.1 Key Features of Tesseract

• Language Support: The Tesseract engine supports over 100 languages, including complex scripts such as Arabic and Chinese.
• Image Preprocessing: It offers extensive image preprocessing capabilities, including deskewing, binarization, and noise reduction, to improve text recognition accuracy.
• Customization Options: Tesseract allows users to fine-tune OCR parameters and train custom models for specific use cases, enhancing accuracy and performance.

3.2 Code Example

using Patagames.Ocr;
using (var api = OcrApi.Create())
{
    api.Init(Patagames.Ocr.Enums.Languages.English);
    string plainText = api.GetTextFromImage(@"C:\Users\buttw\source\repos\ironqr\ironqr\bin\Debug\net5.0\Iron.png");
    Console.WriteLine(plainText);
}

using Patagames.Ocr;
using (var api = OcrApi.Create())
{
    api.Init(Patagames.Ocr.Enums.Languages.English);
    string plainText = api.GetTextFromImage(@"C:\Users\buttw\source\repos\ironqr\ironqr\bin\Debug\net5.0\Iron.png");
    Console.WriteLine(plainText);
}

Imports Patagames.Ocr
Using api = OcrApi.Create()
	api.Init(Patagames.Ocr.Enums.Languages.English)
	Dim plainText As String = api.GetTextFromImage("C:\Users\buttw\source\repos\ironqr\ironqr\bin\Debug\net5.0\Iron.png")
	Console.WriteLine(plainText)
End Using

3.2.1 Output

4. IronOCR

IronOCR, a powerful OCR engine developed by Iron Software, distinguishes itself with its exceptional accuracy, ease of use, and versatile language support. It offers on-premises OCR functionality and supports over 127 languages, making it suitable for global applications. IronOCR leverages advanced machine learning algorithms and cloud vision technology to deliver precise text recognition results, even in challenging scenarios.

4.1 Key Features of IronOCR

• High Accuracy: IronOCR delivers industry-leading accuracy in text recognition, ensuring reliable results across diverse document types and languages.
• Versatile Language Support: It supports over 127 languages and provides comprehensive language packs for seamless multilingual text recognition.
• Simple Integration: IronOCR offers straightforward integration with .NET applications, with intuitive APIs and extensive documentation to streamline the development process with pre-processing, and post-processing original images to extract texts.

4.2 Install IronOCR

Before moving to the coding Example let's see how to install IronOCR using the NuGet Package Manager.

1. In Visual Studio go to Tools Menu and Select NuGet Package Manager.
   2. A new list will appear, here select the NuGet Package Manager for solutions.

3. A new window will appear, go to the 'Browse' tab and click type 'IronOCR' in the search bar.
   4. A list of Packages will appear Select the latest IronOCR package and click on install.

4.3 Code Example (C#)

using IronOcr;
var ocr = new IronTesseract();
ocr.Language = OcrLanguage.English;
var result = ocr.Read("C:\\Users\\buttw\\source\\repos\\ironqr\\ironqr\\bin\\Debug\\net5.0\\Iron.png");
Console.WriteLine(result.Text);

using IronOcr;
var ocr = new IronTesseract();
ocr.Language = OcrLanguage.English;
var result = ocr.Read("C:\\Users\\buttw\\source\\repos\\ironqr\\ironqr\\bin\\Debug\\net5.0\\Iron.png");
Console.WriteLine(result.Text);

Imports IronOcr
Private ocr = New IronTesseract()
ocr.Language = OcrLanguage.English
Dim result = ocr.Read("C:\Users\buttw\source\repos\ironqr\ironqr\bin\Debug\net5.0\Iron.png")
Console.WriteLine(result.Text)

4.3.1 Output

5. Comparative Assessment

5.1 Accuracy and Performance

• Windows OCR Engine and Tesseract Offer decent accuracy but may struggle with complex layouts and handwritten text.
• IronOCR: Excels in accuracy, delivering reliable results across diverse document types and languages, including handwritten text and noisy images.

5.2 Ease of Integration

• Windows OCR Engine: Seamlessly integrates with Windows applications but lacks customization options.
• Tesseract: Requires additional configuration and dependencies for integration but offers extensive customization options.
• IronOCR: Provides simple integration with .NET applications, with intuitive APIs and comprehensive documentation.

5.3 Language Support

• Windows OCR Engine and Tesseract Supports a limited number of languages compared to Tesseract and IronOCR.
• IronOCR: Provides support for over 127 languages, making it suitable for global applications. 6. Conclusion

In conclusion, while Windows OCR Engine and Tesseract are popular choices for text recognition, IronOCR emerges as the most accurate and versatile OCR engine. Its industry-leading accuracy, extensive language support, and simple integration make it a standout solution for businesses and developers seeking reliable OCR functionality. By leveraging IronOCR, organizations can streamline document processing workflows, enhance data extraction accuracy, and unlock valuable insights from scanned documents and images.

IronOCR Offers a free trial. To know more about IronOCR and its features visit here.