.NET MAUI OCR Using IronOCR

Updated: August 2, 2026

Introduction

Microsoft released .NET MAUI (Multi-platform App UI), which is a framework for building cross-platform applications with the .NET Framework. It allows you to write code that runs on Android, iOS, and Windows using the same codebase, saving you time, resources, and effort. .NET MAUI is open source. You can get the source code of the .NET MAUI project with examples on GitHub.

In this How-To Guide, we'll learn how to create an OCR processor app on .NET MAUI using the IronOCR library with examples.

How to Perform OCR in .NET MAUI

Download the C# library for performing OCR in .NET MAUI
Configure the frontend of the MAUI project
Pass the full path of the image using the FilePicker class

Invoke the Read method to perform OCR on the image

Access the extracted text by accessing the Text property and display it

IronOCR: .NET OCR library

IronOCR is a .NET OCR NuGet library that enables developers to easily integrate Optical Character Recognition (OCR) functionality into their projects. Using IronOCR, PDF documents can be scanned and converted into searchable and editable text/data without any loss of data quality. This makes it easy for users to find the information they need from PDF documents and make changes or corrections if necessary.

IronOCR is a comprehensive build of the Tesseract binaries. It provides a native DLL/API that supports all versions of Tesseract (from Tesseract 3 up to Tesseract 5) with one easy install/download.

IronOCR's language support is extensive, with 125 international languages available to users. The English language is installed by default with the tool/DLL. However, you can easily add more languages by installing them through NuGet or by downloading DLLs.

Comparison with Tesseract

IronOCR is specifically designed for C# developers and integrates seamlessly with .NET applications. By contrast, Tesseract is a generic OCR library that requires developers to write their own wrappers to use it with C#. In addition, IronOCR is built for accuracy and speed, thanks to its advanced processing algorithms.

IronOCR comes with comprehensive documentation and technical support, making it easy for even novice developers to get up and running quickly.

IronOCR is designed to deliver higher accuracy than standard Tesseract. Get more info and support about the IronOCR and Tesseract comparison on this YouTube video.

Steps to Create an OCR MAUI app

Follow these steps to create an OCR app in the .NET MAUI framework using IronOCR.

Prerequisites

For creating an OCR app in .NET MAUI, these are the prerequisites:

Visual Studio 2022 (Latest version)
.NET 6 or 7
MAUI packages installed in Visual Studio
A .NET MAUI project running in Visual Studio

Install IronOCR

The first step is to install the IronOCR library using the NuGet Package Manager Console. Open the NuGet Package Manager Console by right-clicking on the solution explorer and executing the following command to install the IronOCR library:

PM > Install-Package IronOcr

Install-Package IronOcr

Frontend Design

We will design the frontend of the application in this section. Open the MainPage.xaml file.

MainPage.xaml

We designate a button that will help us select the image or PDF document for OCR. The button's Clicked property is set to execute the IOCR function which we will define in the next section.

<Button
    x:Name="OCR"
    Text="Click to OCR"
    Clicked="IOCR"
    HorizontalOptions="Center" />

<Button
    x:Name="OCR"
    Text="Click to OCR"
    Clicked="IOCR"
    HorizontalOptions="Center" />

XML

Here, we create an Image element with the name OCRImage. This image box will display the selected file.

<Image
    x:Name="OCRImage"
    SemanticProperties.Description="Selected Image"
    HeightRequest="300"
    HorizontalOptions="Center" />

<Image
    x:Name="OCRImage"
    SemanticProperties.Description="Selected Image"
    HeightRequest="300"
    HorizontalOptions="Center" />

XML

Next, we create an Editor control. It will be used to show the extracted text from the image or PDF document.

<Editor
    x:Name="outputText"
    HorizontalOptions="Center"
    WidthRequest="600"
    HeightRequest="300" />

<Editor
    x:Name="outputText"
    HorizontalOptions="Center"
    WidthRequest="600"
    HeightRequest="300" />

XML

Here is the completed XAML User Interface markup.

<?xml version="1.0" encoding="utf-8" ?>
<ContentPage xmlns="http://schemas.microsoft.com/dotnet/2021/maui"
             xmlns:x="http://schemas.microsoft.com/winfx/2009/xaml"
             x:Class="IronOCR_MAUI_Test.MainPage">

    <ScrollView>
        <VerticalStackLayout
            Spacing="25"
            Padding="30,0"
            VerticalOptions="Center">
            <Button
                x:Name="OCR"
                Text="Click to OCR"
                Clicked="IOCR"
                HorizontalOptions="Center" />
            <Image
                x:Name="OCRImage"
                SemanticProperties.Description="Selected Image"
                HeightRequest="300"
                HorizontalOptions="Center" />

            <Editor
                x:Name="outputText"
                HorizontalOptions="Center"
                WidthRequest="600"
                HeightRequest="300" />
        </VerticalStackLayout>
    </ScrollView>

</ContentPage>

<?xml version="1.0" encoding="utf-8" ?>
<ContentPage xmlns="http://schemas.microsoft.com/dotnet/2021/maui"
             xmlns:x="http://schemas.microsoft.com/winfx/2009/xaml"
             x:Class="IronOCR_MAUI_Test.MainPage">

    <ScrollView>
        <VerticalStackLayout
            Spacing="25"
            Padding="30,0"
            VerticalOptions="Center">
            <Button
                x:Name="OCR"
                Text="Click to OCR"
                Clicked="IOCR"
                HorizontalOptions="Center" />
            <Image
                x:Name="OCRImage"
                SemanticProperties.Description="Selected Image"
                HeightRequest="300"
                HorizontalOptions="Center" />

            <Editor
                x:Name="outputText"
                HorizontalOptions="Center"
                WidthRequest="600"
                HeightRequest="300" />
        </VerticalStackLayout>
    </ScrollView>

</ContentPage>

XML

Now, it's time to write the code for OCR functionality.

Code for OCR using IronOCR

Open the MainPage.xaml.cs class file and write the following function:

MainPage.xaml.cs

private async void IOCR(object sender, EventArgs e)
{
    // Prompt user to select an image using FilePicker
    var images = await FilePicker.Default.PickAsync(new PickOptions
    {
        PickerTitle = "Pick image",
        FileTypes = FilePickerFileType.Images
    });
    
    // Get the full path of the selected image
    var path = images.FullPath.ToString();

    // Display the selected image in the Image control
    OCRImage.Source = path;

    // Create an IronTesseract object to perform OCR
    var ocr = new IronTesseract();
    
    // Perform OCR and extract text from the selected image
    using (var input = new OcrInput())
    {
        input.LoadImage(path); // Load image into the OCR input
        OcrResult result = ocr.Read(input); // Perform OCR
        string text = result.Text; // Extract text

        // Display extracted text in the Editor control
        outputText.Text = text; 
    }
}

private async void IOCR(object sender, EventArgs e)
{
    // Prompt user to select an image using FilePicker
    var images = await FilePicker.Default.PickAsync(new PickOptions
    {
        PickerTitle = "Pick image",
        FileTypes = FilePickerFileType.Images
    });
    
    // Get the full path of the selected image
    var path = images.FullPath.ToString();

    // Display the selected image in the Image control
    OCRImage.Source = path;

    // Create an IronTesseract object to perform OCR
    var ocr = new IronTesseract();
    
    // Perform OCR and extract text from the selected image
    using (var input = new OcrInput())
    {
        input.LoadImage(path); // Load image into the OCR input
        OcrResult result = ocr.Read(input); // Perform OCR
        string text = result.Text; // Extract text

        // Display extracted text in the Editor control
        outputText.Text = text; 
    }
}

Let's break down the above code:

The code uses the FilePicker to allow the user to select an image file from the device. The file picker is configured to only allow images.

var images = await FilePicker.Default.PickAsync(new PickOptions
{
    PickerTitle = "Pick image",
    FileTypes = FilePickerFileType.Images
});
var path = images.FullPath.ToString();

var images = await FilePicker.Default.PickAsync(new PickOptions
{
    PickerTitle = "Pick image",
    FileTypes = FilePickerFileType.Images
});
var path = images.FullPath.ToString();

Dim images = Await FilePicker.Default.PickAsync(New PickOptions With {
	.PickerTitle = "Pick image",
	.FileTypes = FilePickerFileType.Images
})
Dim path = images.FullPath.ToString()

Dim images = Await FilePicker.Default.PickAsync(New PickOptions With {
	.PickerTitle = "Pick image",
	.FileTypes = FilePickerFileType.Images
})
Dim path = images.FullPath.ToString()

The Image control is set to display the selected image using its file path.

OCRImage.Source = path;

OCRImage.Source = path;

OCRImage.Source = path

OCRImage.Source = path

An IronTesseract object is created to perform OCR. The selected image is loaded into an OcrInput object. The Read method is called to extract text from the image, which is then displayed in the Editor control.

var ocr = new IronTesseract();
using (var input = new OcrInput())
{
    input.LoadImage(path);
    OcrResult result = ocr.Read(input);
    string text = result.Text;
    outputText.Text = text; 
}

var ocr = new IronTesseract();
using (var input = new OcrInput())
{
    input.LoadImage(path);
    OcrResult result = ocr.Read(input);
    string text = result.Text;
    outputText.Text = text; 
}

Output

After running the project, the below UI shows up. When you click on the button, it will prompt you to select an image/PDF from any location.

OCR Output

After selecting the image, IronOCR processes the image and shows the recognized words in the Editor control. You can copy the text from the Editor control.

OCR Image

From the results, it shows that IronOCR performs a wonderful job at processing complex images with patterns, showing accurate results. IronOCR is able to detect small details and select the exact letters required using its pre-trained models.

Please note: Running the project in release mode with debugging attached might cause issues. In such cases, you can publish the project as an unpackaged .NET MAUI app, as shown in the link below, to ensure the app works properly.

Conclusion

For further reading, refer to this tutorial which provides additional information about how to use IronOCR to read text from images.

IronOCR is free for development purposes. You can purchase it for a very low price starting from just $999. Check out the pricing plan here.

Frequently Asked Questions

What is IronOCR and how is it used in .NET MAUI applications?

IronOCR is a .NET OCR library that allows developers to integrate Optical Character Recognition functionality into their projects. In .NET MAUI applications, IronOCR can be used to scan and convert PDF documents and images into searchable and editable text, enhancing the app's data processing capabilities.

How do you install IronOCR in a .NET MAUI project?

You can install IronOCR in a .NET MAUI project using the NuGet Package Manager Console. Right-click on the solution explorer and execute the appropriate command in the console to add IronOCR to your project.

What are the prerequisites for creating an OCR app in .NET MAUI using IronOCR?

The prerequisites include having Visual Studio 2022 (latest version), .NET 6 or 7 installed, MAUI packages configured in Visual Studio, and a running .NET MAUI project in your development environment.

How does IronOCR compare to Tesseract for OCR in C# applications?

IronOCR is designed specifically for C# developers, making it easy to integrate into .NET applications without the need for additional wrappers. It offers higher accuracy and speed compared to standard Tesseract, due to its advanced processing algorithms and comprehensive support.

Can IronOCR handle multiple languages for text recognition?

Yes, IronOCR supports 125 international languages for text recognition. The English language is installed by default, and additional languages can be added via NuGet or by downloading associated DLLs.

What types of files can be processed with IronOCR in a .NET MAUI application?

IronOCR can process various image files and PDF documents within a .NET MAUI application, allowing for effective OCR functionality across different file formats.

Is there any documentation or support available for developers using IronOCR?

Yes, IronOCR comes with comprehensive documentation and technical support, making it easy for developers at any level to utilize its functionality effectively in their projects.

What are the steps to perform OCR on an image in a .NET MAUI app using IronOCR?

The steps include downloading the IronOCR library, configuring the MAUI project's frontend, using the FilePicker to select an image, and utilizing IronOCR's Read method to extract and display text from the image.

Does IronOCR offer a trial or development version for testing?

IronOCR is free for development purposes, and you can purchase it for deployment starting from a low pricing plan. Detailed pricing information is available on their licensing page.

How does the OCR output display in a .NET MAUI application using IronOCR?

After processing an image using IronOCR in a .NET MAUI application, the recognized text is displayed within an Editor control, allowing users to view and copy the extracted text for further use.

Curtis Chau

Chat with engineering team now

Technical Writer

Curtis Chau holds a Bachelor’s degree in Computer Science (Carleton University) and specializes in front-end development with expertise in Node.js, TypeScript, JavaScript, and React. Passionate about crafting intuitive and aesthetically pleasing user interfaces, Curtis enjoys working with modern frameworks and creating well-structured, visually appealing manuals.

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