using IronOcr; using IronSoftware.Drawing; // We can delve deep into OCR results as an object model of // Pages, Barcodes, Paragraphs, Lines, Words and Characters // This allows us to explore, export and draw OCR content using other APIs/ var ocrTesseract = new IronTesseract(); ocrTesseract.Configuration.ReadBarCodes = true; using var ocrInput = new OcrInput(); var pages = new int[] { 1, 2 }; ocrInput.LoadImageFrames("example.tiff", pages); OcrResult ocrResult = ocrTesseract.Read(ocrInput); foreach (var page in ocrResult.Pages) { // Page object int PageNumber = page.PageNumber; string PageText = page.Text; int PageWordCount = page.WordCount; // null if we dont set Ocr.Configuration.ReadBarCodes = true; OcrResult.Barcode[] Barcodes = page.Barcodes; AnyBitmap PageImage = page.ToBitmap(ocrInput); int PageWidth = page.Width; int PageHeight = page.Height; double PageRotation = page.Rotation; // angular correction in degrees from OcrInput.Deskew() foreach (var paragraph in page.Paragraphs) { // Pages -> Paragraphs int ParagraphNumber = paragraph.ParagraphNumber; string ParagraphText = paragraph.Text; AnyBitmap ParagraphImage = paragraph.ToBitmap(ocrInput); int ParagraphX_location = paragraph.X; int ParagraphY_location = paragraph.Y; int ParagraphWidth = paragraph.Width; int ParagraphHeight = paragraph.Height; double ParagraphOcrAccuracy = paragraph.Confidence; OcrResult.TextFlow paragrapthText_direction = paragraph.TextDirection; foreach (var line in paragraph.Lines) { // Pages -> Paragraphs -> Lines int LineNumber = line.LineNumber; string LineText = line.Text; AnyBitmap LineImage = line.ToBitmap(ocrInput); int LineX_location = line.X; int LineY_location = line.Y; int LineWidth = line.Width; int LineHeight = line.Height; double LineOcrAccuracy = line.Confidence; double LineSkew = line.BaselineAngle; double LineOffset = line.BaselineOffset; foreach (var word in line.Words) { // Pages -> Paragraphs -> Lines -> Words int WordNumber = word.WordNumber; string WordText = word.Text; AnyBitmap WordImage = word.ToBitmap(ocrInput); int WordX_location = word.X; int WordY_location = word.Y; int WordWidth = word.Width; int WordHeight = word.Height; double WordOcrAccuracy = word.Confidence; foreach (var character in word.Characters) { // Pages -> Paragraphs -> Lines -> Words -> Characters int CharacterNumber = character.CharacterNumber; string CharacterText = character.Text; AnyBitmap CharacterImage = character.ToBitmap(ocrInput); int CharacterX_location = character.X; int CharacterY_location = character.Y; int CharacterWidth = character.Width; int CharacterHeight = character.Height; double CharacterOcrAccuracy = character.Confidence; // Output alternative symbols choices and their probability. // Very useful for spellchecking OcrResult.Choice[] Choices = character.Choices; } } } } }

Updated February 12, 2024

OCR Automation (OCR License Plate in C# Tutorial)

Introduction

The automation of text extraction from images and scanned files through Optical Character Recognition (OCR) technology has brought about a revolutionary transformation in how businesses manage extensive document volumes. OCR automation enhances efficiency, and accuracy, and reduces manual effort in data entry tasks.

This article will explore the concept of OCR automation, its benefits, and showcase an example using an OCR tool, along with its pros and cons. Finally, IronOCR is recommended as a powerful solution for OCR automation.

Understanding OCR Automation

OCR automation involves the use of OCR software to convert different types of documents, such as scanned paper documents, PDFs, or images, into editable and searchable data. It also helps organize unstructured data by extracting only relevant data and hence converting it to structured data to be used by business processes. This technology enables business processes to extract valuable information from documents rapidly, leading to improved productivity and reduced error rates.

Benefits of OCR Automation

Increased Efficiency: Manual data entry is time-consuming and prone to errors. OCR is like robotic process automation that speeds up the process of data capture, extracting information from documents, and hence significantly reducing the time required for data entry tasks.
Accuracy Improvement: Automation eliminates the risk of human error associated with manual data entry. OCR technology is designed to recognize characters with high precision, resulting in accurate data extraction.
Cost Reduction: By automating repetitive and time-consuming tasks, OCR technology reduces labor costs associated with manual data entry. This cost-effective solution allows organizations to allocate resources more efficiently for extracting data.
Enhanced Searchability: OCR-processed documents become searchable, making it easier to locate specific information within large datasets. This improves data processing tasks and decision-making processes.

Example of OCR Automation

Let's consider a scenario where a company receives a large number of invoices daily. Manually inputting data from these invoices into a database is time-consuming and prone to errors. These invoices are mostly well-structured data. With robotic process automation, the company can extract relevant information such as invoice numbers, dates, and amounts automatically.

OCR Tool Example: Tesseract OCR

Tesseract OCR is an open-source OCR engine widely used for text recognition. It is renowned for its accuracy in recognizing text from images and scanned documents. Tesseract is written in C++ but has various bindings for different programming languages, making it accessible for developers across platforms.

How Tesseract OCR Automates the OCR Process

Image Pre-processing:
- Tesseract OCR can handle various image formats, including scanned documents and images.
- Before processing, images may undergo pre-processing techniques like resizing, binarization, or noise reduction to enhance recognition accuracy.
Page Layout Analysis:
- Tesseract performs page layout analysis to identify text regions, columns, and blocks within a document.
- This analysis helps Tesseract recognize the structure of the document, improving the accuracy of text extraction.
Character Recognition:
- Tesseract employs a combination of neural networks and pattern matching to recognize characters.
- It supports multiple languages and can be trained for specific fonts or language scripts.
Output Formatting:
- Tesseract outputs recognized text in a structured format, making it easier for further processing or integration into databases and applications.

How to Use Tesseract OCR in Windows

Using Tesseract OCR in Windows involves a few steps. Here's a basic guide:

Install Tesseract OCR:
- Download the Tesseract installer for Windows from the official GitHub UB Mannheim repository: Tesseract OCR exe.
- Run the installer and follow the on-screen instructions to complete the installation.
Install Tesseract OCR Windows Application
- Select the location and remember the path of installation as it will be used later to set in the Path variable.
Update the path of installation
Set Up Environment Variables:
- Add the Tesseract installation directory to the system's PATH environment variable. This ensures that the Tesseract executable can be accessed from any command prompt window.
Navigate to Environment Variables
Accessing PATH environment variable
Modify PATH environment variable
Command-Line Usage:
- Open a command prompt window and navigate to the directory containing your images or scanned documents.
- Use the following command to perform OCR on an image and output the result to a text file:
```
tesseract input_image.png output_text.txt
```
```
tesseract input_image.png output_text.txt
```
```
'INSTANT VB TODO TASK: The following line uses invalid syntax:
'tesseract input_image.png output_text.txt
```
VB C#
Replace input_image.png with the name of your image file and output_text.txt with the desired name for the output text file.
Example with Invoice Processing:
- Let's say you have a folder named Invoices containing multiple invoice images.
- Open a command prompt and navigate to the directory containing the Invoices folder.
- Use a loop to process all images in the folder:
```
for %i in (Invoices\*.png) do tesseract %i Output\%~ni.txt
```
```
for %i in (Invoices\*.png) do tesseract %i Output\%~ni.txt
```
```
for Mod i in (Invoices\*.png)
	Do
'INSTANT VB TODO TASK: The following line uses invalid syntax:
'		tesseract %i Output\%~ni.txt
```
VB C#
This command processes each image in the Invoices folder and outputs the recognized text into corresponding text files in the Output folder.

Pros

Accuracy: Tesseract OCR provides high accuracy in recognizing text, making it suitable for various applications.
Language Support: It supports a wide range of languages, making it versatile for global applications.
Community Support: Being an open-source project, Tesseract OCR has a large and active community that contributes to its improvement.

Cons

User Interface: Tesseract OCR is primarily a command-line tool, which might be less user-friendly for those accustomed to graphical interfaces.
Training Complexity: Training Tesseract for specific fonts or languages can be complex and requires technical expertise.

Introducing IronOCR

IronOCR is a comprehensive OCR solution that stands out for its ease of use, accuracy, and robust features. Designed to simplify the integration of OCR into .NET applications, IronOCR offers a comprehensive set of features that make it a powerful tool for automating text recognition.

IronOCR includes advanced image processing capabilities, allowing developers to optimize images before OCR processing. Image pre-processing features contribute to improved text recognition accuracy, especially in scenarios where image quality varies.

Pros of IronOCR

Easy Integration: IronOCR seamlessly integrates into .NET applications, providing a simple and intuitive interface for developers.
High Accuracy: IronOCR leverages advanced algorithms to achieve high accuracy in text recognition, ensuring reliable data extraction.
Versatility: It supports a wide range of document formats, including PDFs and images, making it suitable for diverse applications.
Automatic Correction: IronOCR includes features for the automatic correction of recognized text, minimizing errors in extracted data.

Cons of IronOCR

Cost: While IronOCR offers a free trial, the full version comes with a cost. However, the investment may be justified by the product's robust features and support.

IronOCR Code Example

Let's consider a scenario where you have a C# application that needs to extract text from an invoice image using IronOCR Tesseract 5 for .NET. Below is a simple code example demonstrating how to achieve this:

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    input.LoadImage("invoice_image.png");
    input.AddPdf("invoice_pdf.pdf");

    OcrResult result = ocr.Read(input);
    string text = result.Text;
}

using IronOcr;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    input.LoadImage("invoice_image.png");
    input.AddPdf("invoice_pdf.pdf");

    OcrResult result = ocr.Read(input);
    string text = result.Text;
}

Imports IronOcr

Private ocr = New IronTesseract()

Using input = New OcrInput()
	input.LoadImage("invoice_image.png")
	input.AddPdf("invoice_pdf.pdf")

	Dim result As OcrResult = ocr.Read(input)
	Dim text As String = result.Text
End Using

VB C#

For more detailed information on OCR automation projects using IronOCR, please visit the tutorial on OCR License Plate in C#.

The IronOCR documentation page serves as a comprehensive resource for developers, offering clear and detailed guidance on integrating, configuring, and optimizing the IronOCR library for seamless OCR automation in .NET applications. With thorough documentation, examples, and API references, developers can efficiently harness the power of IronOCR to enhance text recognition accuracy and streamline document processing workflows.

Conclusion

OCR automation is a powerful tool for businesses looking to streamline document processing, reduce manual efforts, and enhance accuracy. While there are various OCR solutions available, each has its strengths and weaknesses. Tesseract OCR, as an open-source option, is powerful but may be less user-friendly. On the other hand, IronOCR provides a comprehensive solution with easy integration, high accuracy, and versatile features.

In conclusion, the choice of OCR tool depends on the specific needs and preferences of the user or organization. For those seeking a robust, user-friendly OCR solution with advanced features, IronOCR stands out as a compelling choice in the field of OCR automation.

IronOCR offers a free trial license for users to explore and evaluate its capabilities. However, for commercial use, a licensing fee starting from $599 is required. To download the software and obtain a commercial license, visit the official IronOCR website.