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Tag Archives: OCR
Extract Texts from Images – Add OCR and OMR Technology in Java using Aspose.OCR IntelliJ Maven Plugin
New Plugin – Aspose.OCR Java for IntelliJ IDEA (Maven) v.1.0.0.0 released!
Aspose releases New IntelliJ IDEA Plugin to utilize Aspose.OCR for Java API in java applications easily for dealing with OCR and OMR images.
Aspose.OCR is aimed at developers who need to find text in image files from within their own applications. It allows developers to extract text from images quickly and easily.
While OMR features can be used to process questionnaires, ballots, educational tests and ordering sheets, where the … Continue Reading
Aspose.OCR Java For Ruby Examples – Dealing with OCR and OMR Images
Aspose.OCR for Java is an optical character & marker recognition component allowing the programmers to add OCR & OMR technology into their Java applications quickly and easily.
OMR features can be used to process questionnaires, ballots, educational tests and ordering sheets, where the documents to be processed are filled in by hand, and scanned images of such forms are used for marker recognition.
We are pleased to announce “Aspose.OCR Java for Ruby”, a new gem for Ruby developers. … Continue Reading
Posted in Aspose.OCR Product Family Tagged Aspose.OCR for Java, OCR, OMR, OcrEngine, Ruby examples, RubyGem
Noise Removal Filters and Second Guess a Symbol in OCR using C#
We are pleased to announce the release of Aspose.OCR for .NET 1.3.0. In this release, we have introduced two new features. Firstly, noise removal filters are included in the public API. Now you can process images with these filters before running recognition. This helps improve text recognition accuracy.
Secondly, we’ve added a feature for exposing a second possible guess for a symbol. The following code snippet shows how the second guess properties work.
OcrEngine ocr = new OcrEngine();
//ocr.Config.
ocr.Config.UseDefaultDictionaries
… Continue Reading Posted in Aspose.OCR Product Family Tagged .NET, Aspose.OCR, Noise Removal Filters, OCR, Second guess of recognized symbol, product release
Multipage image recognition and support of more image formats using Aspose.OCR for .NET 1.2.0
Aspose.OCR for .NET 1.2.0 has been released. We are pleased to announce that support of more image formats is included in this release: JPG, JPEG, PNG and GIF. This expands the scope of the Aspose.OCR API. This release supports recognition of multipage TIFF image with the introduction of a new property for OcrEngin-ProcessAllPages. This release also supports recognition of text in form fields, that is, tables. The text recognition accuracy is above 90% and is 100% in some cases with … Continue Reading
Posted in Aspose.OCR Product Family Tagged .NET, Aspose.OCR, Multipage Image Recognition, OCR, product release
Extract hOCR Text or Recognize Characters from Images in your Java Applications
We are pleased to announce our new product Aspose.OCR for Java. Aspose.OCR for Java is an optical character recognition component that allows developers to extract text from image files. You can extract text in hOCR format which not only gives you the extracted text but other text information (font and style etc.) as well.
Aspose.OCR for Java is aimed at the developers who need to add OCR functionality in their Java applications and provides a better performance. The API is … Continue Reading
Aspose adds character recognition to their .NET toolbox with Aspose.OCR
Australia, Sydney – 5 July, 2011 – Aspose.OCR for .NET is a character recognition component that allows software developers to add OCR functionality to their ASP .NET web applications, web services and Windows applications. It provides a simple set of classes for controlling character recognition tasks.
Efficient character recognition
Extracting text from Microsoft Word or Adobe PDF files is relatively simple. In those file formats the text is separate, stored as content with formatting markup. Turning images into text is … Continue Reading
Posted in Aspose.Total Product Family, Aspose.OCR Product Family, News Release Tagged .NET, OCR, new product, news, optical character recognition, press release