To Recognize Text From Image in C#, the first step is to install Iron OCR. This is most easily achieved using the NuGet Package Manager using the ID name OCR for the package we wish to install. The Auto OCR class is a .NET class allowing OCR to be achieved in a single line of code. It can read text from images in C# .Net with very little setup, and Iron OCR will automatically make a best guess at all of the correct configuration and image cleanup operations required for a good OCR operation and clean text to be extracted from an image. The Advanced OCR class can be used for advanced OCR operations to read text from an image in c#. It allows us to extract text from images, TIFFs, scans and photographs, and even PDF documents. Within the tutorial, we have source code for dealing with different situations where we have low, medium, and high quality scans, and also look at how we can correct for digital noise, skew, perspective, and rotation. The next section of the tutorial shows how we can optimize Iron OCR in C# for the fastest result, although there is always a balance between speed and OCR accuracy. We move forward to look at how we can use Iron OCR and C# to extract international text from documents using non-English scripts. We show how to install language packs such as Arabic, Spanish, and Chinese. The last part of the tutorial shows how we can drill down into the OCR results using C# code. This allows us to see pages, paragraphs, lines, words, characters, and even barcodes found within a document. We can look at their typeface, statistical accuracy, location, and even return an image for that object. We have learnt how to convert an image to text in c#. This project provides full source code available as a ZIP file as well as a GIT Repository where the C# source code can be viewed and modified by developers.
|License||Free to try|
|File Size||3.89 MB|
|Operating System||Windows XP Windows Vista Windows Windows 10 Windows 7 Windows 2003 Windows 8|
|System Requirements||.Net Framework 4.0, C++ Runtime Environment|