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Published July 23, 2023

Invoice OCR API (Developer Tutorial)

Invoice Optical Character Recognition (OCR) API is a technology that utilizes machine learning and computer vision techniques to extract data from invoices and other financial documents. By converting the text, structured data and numbers on an invoice into machine-readable format, OCR enables automated processing, analysis, and integration of invoice data into various business systems.

Traditionally, manual data entry has been a time-consuming and error-prone process when dealing with invoices. Businesses of all sizes, from small enterprises to large corporations, have to handle a significant volume of invoices, which often results in processing delays, increased costs to process invoices, and a higher risk of human error. However, with the advent of OCR technology, these challenges can be effectively addressed. OCR systems are designed to recognize and interpret various types of information present in invoices, such as vendor details, invoice numbers, dates, line items, quantities, prices, and totals. Through the use of advanced algorithms, OCR algorithms can accurately identify and extract this information, even from scanned or digitally generated invoices.

In this article we will use top of the line invoice OCR API named IronOCR.

1. IronOCR

IronOCR is a robust Optical Character Recognition (OCR) library developed by Iron Software, offering developers an extensive range of tools and functionalities to integrate OCR capabilities into their applications. By leveraging advanced machine learning algorithms and computer vision techniques, IronOCR accurately extracts text and data from scanned documents, images, unstructured invoices and PDF files, enabling automated processing of extracted data and information retrieval. With its straightforward APIs, IronOCR seamlessly integrates into various programming languages and platforms, empowering businesses to automate manual data entry, reduce errors, and improve efficiency for financial and administrative processes. The extracted text and data can be processed, analyzed, and integrated into existing business systems, facilitating better decision-making and enhancing productivity. Additional features like image preprocessing, barcode recognition, and PDF document or CSV file parsing expand the library's versatility, catering to complex document requirements. Overall, IronOCR is a comprehensive OCR solution that empowers developers to incorporate powerful text recognition capabilities into their applications and workflows.

2. Prerequisites

Before you can start working with IronOCR, there are a few prerequisites that need to be in place. These prerequisites include:

1. Ensure that you have a suitable development environment set up on your computer. This typically involves having an Integrated Development Environment (IDE) such as Visual Studio installed.
2. It's important to have a basic understanding of the C# programming language. This will enable you to comprehend and modify the code examples provided in the article effectively.
3. You'll need to have the IronOCR library installed in your project. This can be accomplished by using the NuGet Package Manager within Visual Studio or through the command line interface.

By ensuring that these prerequisites are met, you'll be ready to dive into the process of working with IronOCR.

3. Creating a New Visual Studio Project

To get started with IronOCR, we need to create a new Visual Studio project.

Open Visual Studio and go to Files, then hover on New, and click on Project.

In the new window, select Console application and click on Next.

A new window will appear, write the name of your new project, location and click on Next.

Finally, provide the Target framework and click on Create.

Now your new Visual Studio project is created. Let's install IronOCR.

4. Installing IronOCR

There are several methods for downloading and installing the IronOCR library. But we'll only go through two of them.

1. Using the Visual Studio NuGet Package Manager
2. Using the Visual Studio Command Line

4.1. Using the Visual Studio NuGet Package Manager

IronOCR may be included in a C# project by utilizing the Visual Studio NuGet Package Manager.

Navigate to the NuGet Package Manager graphical user interface by selecting Tools > NuGet Package Manager > Manage NuGet Packages for Solutions...

After this, a new window will appear. Search for IronOCR and install the package in the project.

Additional language packs for IronOCR can also be installed using the same method described above.

4.2. Using the Visual Studio Command-Line

1. In Visual Studio, go to Tools > NuGet Package Manager > Package Manager Console

2. Enter the following line in the package manager console tab:

   PM > Install-Package IronOcr

The package will now download/install in the current project and be ready to use.

5. Extract data from Invoice using IronOCR

Using IronOCR, you can easily extract data from invoices with just few lines of code and use that data extraction for further processes like data entry. This will replace manual data entry and many more.

First we need an example invoice to extract text from.

Now, let's write the code to extract all the data from this invoice.

using IronOcr;
using System;

var Ocr = new IronTesseract();
using (var Input = new OcrInput(@"r2.png"))
{
    var Result = Ocr.Read(Input);
    Console.WriteLine(Result.Text);
}

using IronOcr;
using System;

var Ocr = new IronTesseract();
using (var Input = new OcrInput(@"r2.png"))
{
    var Result = Ocr.Read(Input);
    Console.WriteLine(Result.Text);
}

IRON VB CONVERTER ERROR developers@ironsoftware.com

The above code gets input in a form of image and then extracts data from that image using Ocr.Read(Input) method.

5.1. Invoice Processing to extract specific data from invoices

You can also extract specific data from invoices like customer invoice number. Below is the code to extract customer invoice number from invoice.

using IronOcr;
using System;
using System.Text.RegularExpressions;

var Ocr = new IronTesseract();
using (var Input = new OcrInput(@"r2.png"))
{
    var Result = Ocr.Read(Input);
    var LinePattern = @"INV\/\d{4}\/\d{5}";
    var LineMatch = Regex.Match(Result.Text, LinePattern);
    if (LineMatch.Success)
    {
        var LineValue = LineMatch.Value;
        Console.WriteLine("Customer Invoice number: " + LineValue);
    }

}

using IronOcr;
using System;
using System.Text.RegularExpressions;

var Ocr = new IronTesseract();
using (var Input = new OcrInput(@"r2.png"))
{
    var Result = Ocr.Read(Input);
    var LinePattern = @"INV\/\d{4}\/\d{5}";
    var LineMatch = Regex.Match(Result.Text, LinePattern);
    if (LineMatch.Success)
    {
        var LineValue = LineMatch.Value;
        Console.WriteLine("Customer Invoice number: " + LineValue);
    }

}

IRON VB CONVERTER ERROR developers@ironsoftware.com

6. Conclusion

Invoice OCR API, facilitated by advanced libraries like IronOCR, has revolutionized the extraction of data from invoices. By leveraging machine learning and computer vision, OCR technology automates the process of converting invoice text and numbers into machine-readable format. IronOCR, a powerful OCR library developed by Iron Software, provides developers with comprehensive tools to integrate OCR capabilities seamlessly for processing invoices. By following the necessary prerequisites and utilizing IronOCR, businesses can effortlessly extract specific data or obtain complete structured data from invoices, enabling further analysis, integration, and improved business processes. Invoice OCR with IronOCR offers a robust solution for automating invoice processing, improving accuracy, and optimizing operational workflows such as accounts payable processes. Invoice data extraction to process scanned invoices uses automate invoice processing and the extracted data can be used for automating data entry using invoice OCR technology.

For more information on IronOCR, visit this link. For tutorial on invoice OCR, visit the following link. To know about how to use computer vision to find text such as invoice fields, visit here.