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; } } } } }

Published December 13, 2023

OCR Foto (Beginner Tutorial)

Introduction

Optical Character Recognition (OCR) technology has revolutionized the way we interact with text in the digital world. OCR Photo tools enable the ability to convert images to text, making it easier to digitize printed or handwritten notes.

In this article, we will explore four online OCR tools—both free and paid—and conclude with an introduction to IronOCR, showcasing how OCR can be implemented programmatically in C#.

1. Google Vision API

Google Vision API provides a powerful OCR solution to create image to text converter provided by Google. It supports image and PDF text extraction and can recognize text in multiple languages.

OCR Foto (Beginner Tutorial): Figure 1

Pros

High accuracy
Language support
Integration with other Google Cloud services.

Cons

Requires API key
Not entirely free beyond a certain usage threshold.

Step 1 Obtain API Key

Visit the Google Cloud Console.
Create a new project or select an existing one.
Enable the Cloud Vision API and generate an API key.

Step 2 Make API Request

Use a tool like cURL or a programming language of your choice to make an HTTP POST request.
Include the image file or URL in the request payload.

curl -s -X POST -H "Content-Type: application/json" \
    -H "Authorization: Bearer YOUR_API_KEY" \
    --data-binary @path/to/your/image.jpg \
    "https://vision.googleapis.com/v1/images:annotate?key=YOUR_API_KEY"

Step 3 Parse Results

Extract the recognized text from the API response.

{
  "responses": [
    {
      "textAnnotations": [
        {
          "description": "Hello World!",
          "boundingPoly": { /* bounding box coordinates */ }
        }
      ]
    }
  ]
}

2. Tesseract OCR

Tesseract is an open-source OCR engine developed by Google. It supports over 100 languages and is widely used for its accuracy and flexibility. It helps converting images from multiple file formats and even convert scanned handwriting images to editable text.

OCR Foto (Beginner Tutorial): Figure 2

Pros

Open-source
High accuracy
Community support

Cons

May require additional tools for integration
Might need image pre-processing for optimal results.

Step 1 Install Tesseract

Download and install Tesseract OCR from the official GitHub repository.
Add the tesseract folder to Path environment variable to get access anywhere in the terminal.

Step 2 Run OCR on Image

Open a terminal and navigate to the folder containing the image.
Execute the following command:

tesseract path/to/your/image.jpg output.txt

tesseract path/to/your/image.jpg output.txt

'INSTANT VB TODO TASK: The following line uses invalid syntax:
'tesseract path/@to/your/image.jpg output.txt

VB C#

Step 3 View Results

Open the generated text file (output.txt) to see the extracted text.

3. ABBYY FineReader Online

ABBYY FineReader Online is a cloud-based OCR service that allows users to convert scanned documents and images into editable formats.

This online tool provides free to use OCR based text converter online for extracting text from images without any hassle.

OCR Foto (Beginner Tutorial): Figure 3

Pros

User-friendly image OCR tool
Supports various input formats
Preserves document formatting

Cons

Limited free usage
Internet connection required

Step 1 Visit ABBYY FineReader Online

Go to the ABBYY FineReader Online website.
Download the free trial for Windows or Mac.
Install the software and follow the given steps.

Step 2 Upload Image

Click on the "Choose file" button and upload your image.

Step 3 Process Image

Wait for the image to be processed. The tool will automatically extract text.

Step 4 Edit Text

Save the extracted text or use the editor to make any necessary corrections
Save in Word, Excel and Text formats.

4. Online OCR

Online OCR is a web-based OCR service that supports multiple languages for online image to text conversion. Users can upload images directly from their devices or provide URLs.

Pros

Simple user interface
Supports various input formats
Free to use with limitations

Cons

Limited free features
Dependent on internet connectivity

Step 1 Visit Online OCR

Go to the Online OCR website.

Step 2 Upload Image

Click on the "Select file" button and upload your image.

OCR Foto (Beginner Tutorial): Figure 4

Step 3 Choose Language and Output Format

Select the language and Output format of the text in the image.

OCR Foto (Beginner Tutorial): Figure 5

Step 4 Start OCR

Click on the "Convert" button to start the OCR process.

Step 5 Download Text

Once the process is complete, download the extracted text from the provided link.

OCR Foto (Beginner Tutorial): Figure 6

Introduction to IronOCR in C#

Now, let's delve into IronOCR, a powerful OCR library for C# that provides developers with the tools to implement OCR functionality seamlessly. IronOCR is a leading OCR library for C# developed by the Iron Software team.

IronOCR stands out as a robust Optical Character Recognition (OCR) library designed specifically for C# developers, providing a powerful suite of features for accurate and seamless text extraction from images.

Known for its reliability and efficiency, IronOCR has gained popularity among C# developers seeking a comprehensive solution for text extraction from images and documents.

With a focus on accuracy and versatility, IronOCR has become a go-to choice for projects ranging from document management systems to data extraction applications.

Leveraging advanced OCR algorithms, IronOCR excels in accurately deciphering text from various image formats, including JPEG, PNG, and TIFF. Its versatility extends to multi-language support, making it a valuable tool for applications that cater to diverse linguistic needs.

This library seamlessly integrates with popular .NET frameworks, streamlining the implementation of OCR functionality within C# applications.

Whether you're working with scanned documents or images, IronOCR's comprehensive features empower developers to effortlessly incorporate OCR capabilities into their projects.

IronOCR Features in Detail

Advanced OCR Algorithms: IronOCR employs sophisticated OCR algorithms that go beyond basic character recognition, ensuring high accuracy even in complex scenarios.
Image Format Support: Developers can take advantage of IronOCR's support for a variety of image formats, such as JPEG, PNG, and TIFF, providing flexibility in handling diverse visual content.
Multi-language Support: Recognizing the global nature of applications, IronOCR is equipped with multi-language support, enabling the extraction of text in different languages with precision.
PDF Text Extraction: In addition to images, IronOCR extends its capabilities to extract text from PDF documents, enhancing its applicability in scenarios where documents are stored in digital formats.
Integration with .NET Frameworks: IronOCR seamlessly integrates with popular .NET frameworks, making it easy for C# developers to incorporate OCR functionality into their projects without the hassle of extensive configuration.

Implementing OCR with IronOCR in C#

Below is a simple example of using IronOCR in C# to extract text from an image:

using IronOcr;
string imageText = new IronTesseract().Read(@"images\image.png").Text;

using IronOcr;
string imageText = new IronTesseract().Read(@"images\image.png").Text;

Imports IronOcr
Private imageText As String = (New IronTesseract()).Read("images\image.png").Text

VB C#

This simple C# code snippet demonstrates how IronOCR can be used to read text from an image file. Developers can further customize the OCR process based on their specific requirements.

For detailed information on advanced functionality of IronOCR, please visit the documentation page.

Conclusion

OCR photo tools play a vital role in digitizing textual content from images. While various online tools offer convenience, IronOCR provides developers with a powerful and flexible solution for integrating OCR capabilities into their C# applications.

The choice between online tools and programmatically implemented libraries depends on factors such as accuracy requirements, customization needs, and the level of control developers seek over the OCR process.

IronOCR does offer a free trial is required. Download the software from here.