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 August 30, 2023

How to Use OCR text Recognition (Beginner Tutorial)

In our modern digital landscape, understanding the ins and outs of OCR (optical character recognition) text recognition holds significant importance. This article acts as a user-friendly guide, breaking down the intricacies of OCR technology and its practical applications, including its ability to recognize text from a scanned document or PDF file. It walks you through the process of selecting suitable OCR tools, enhancing their performance, and tackling complex scenarios like diverse languages or less-than-optimal documents. Additionally, it delves into responsible OCR usage and ethical considerations. Whether you're a newcomer or already acquainted with the concept, this guide equips you with the knowledge to effectively harness OCR capabilities and simplify tasks in our increasingly digital era to extract text from scanned documents. For this purpose, IronOCR is the best OCR library out there.

Understanding OCR (Optical Character Recognition)

Imagine being able to scan a printed document or even a handwritten note and instantly convert it into editable digital text. That's the magic of OCR at work. OCR is a technology that uses pattern recognition and machine learning algorithms to recognize and extract text from images or scanned documents. This enables the transformation of printed materials into searchable, editable, and shareable digital formats.

OCR.space

OCR.space is a cutting-edge online platform that brings the power of OCR to your fingertips. With its user-friendly interface and powerful algorithms, OCR.space empowers users to effortlessly convert images and scanned documents into text, opening up a world of possibilities for efficient information management. Whether you're a student, professional, researcher, or anyone dealing with printed content, OCR.space simplifies the process of digitizing text, making it an essential tool in today's digital age.

Using OCR.space

Performing OCR (Optical Character Recognition) using the OCR.space website is a straightforward process that allows you to convert any scanned image or any scanned paper document into editable text. Follow these steps to perform OCR using the OCR.space website:

Access the OCR.space Website: Open your preferred web browser and navigate to the OCR.space website at https://ocr.space/.
Upload Your Image: Click on the "Choose File" button or drag and drop your image directly onto the designated area on the website. The image can be in various formats, such as JPG, PNG, GIF, or PDF.
Start OCR Process: After uploading your image and configuring optional settings, click the "Start OCR!" button. The OCR.space website will process your image and extract the recognized text.
Review and Download Results: Once the OCR process is complete, you'll be presented with the extracted text on the website. Review the text to ensure accuracy and make any necessary adjustments by manual data entry.
Download Text: If you're satisfied with the results, click the "Download" button to save the extracted text to your computer. Depending on your selected output format, you'll receive a plain text file or a searchable PDF.
Save or Share Results: You can now save the extracted text to your preferred location on your computer or share it with others as needed.

This is how you use OCR.space and an OCR engine to extract text from an image file.

Introducing IronOCR

IronOCR stands as a revolutionary solution in the realm of Optical Character Recognition (OCR) - intelligent character recognition, offering a blend of sophistication and user-friendliness. With its robust capabilities, IronOCR enables the conversion of images and scanned documents into machine-readable text with remarkable accuracy. Whether handling invoices, extracting text from printed documents or handwritten notes, archival documents, or data entry tasks, IronOCR's intuitive interface and powerful algorithms streamline the process, catering to both tech-savvy professionals and newcomers to OCR technology. This tool's ability to seamlessly bridge the gap between visual content and digital text is reshaping how information is accessed, manipulated, and harnessed across industries.

Installing IronOCR

You can easily install IronOCR using the NuGet Package Manager console, just by running the following command, or you can download it directly from the NuGet Website.

Install-Package IronOcr

Extracting Text Using IronOCR

In this section, we will see how you can easily extract text from images using IronOCR. The source code below shows how to extract text from the image.

using IronOcr;
using System;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    input.AddImage("r3.png");
    OcrResult result = ocr.Read(input);
    string text = result.Text;
    Console.WriteLine(result.Text);
}

using IronOcr;
using System;

var ocr = new IronTesseract();

using (var input = new OcrInput())
{
    input.AddImage("r3.png");
    OcrResult result = ocr.Read(input);
    string text = result.Text;
    Console.WriteLine(result.Text);
}

Imports IronOcr
Imports System

Private ocr = New IronTesseract()

Using input = New OcrInput()
	input.AddImage("r3.png")
	Dim result As OcrResult = ocr.Read(input)
	Dim text As String = result.Text
	Console.WriteLine(result.Text)
End Using

VB C#

Output

Here is the output screenshot of automatic text recognition or recognized text.

How to Use OCR Text Recognition (Beginner Tutorial): Figure 5

Conclusion

In today's digital age, a firm grasp of Optical Character Recognition (OCR) text recognition is paramount, and this guide adeptly navigates its complexities and applications. From demystifying OCR's functionality to practical tool selection, performance enhancement, and ethical considerations, the guide empowers users to adeptly utilize platforms like OCR.space and IronOCR. By elucidating the step-by-step process of employing OCR.space for text extraction and introducing the transformative capabilities of IronOCR, the guide equips both beginners and experts to seamlessly integrate OCR tools into their workflows. Ultimately, this guide underscores OCR's pivotal role in simplifying text extraction from scanned documents, ushering users into an era of enhanced digital proficiency.

As we highlighted, IronOCR is a market-leading OCR software that seamlessly integrates visual content and digital text, revolutionizing the way information is accessed, manipulated, and utilized across various sectors. A more detailed tutorial on IronOCR can be found on IronOCR's website.