Aspose.Total Java for IntelliJ IDEA v1.4 released with more new Source Code Examples

[![][1] version 1.4 has been released. The plugin provides useful wizards to easily start working with [Aspose.Total Java APIs][2]. Through wizards you can select and download latest [Aspose Java APIs][3] and sample example codes for using them. Visit [JetBrains - IntelliJ IDEA Plugin Portal][4] to download and install Aspose.Total Java for IntelliJ IDEA latest v1.4. Aspose Docs are always available for help in Download, Installation and Usage of Aspose.Total Java for IntelliJ IDEA.
December 2, 2015 · 3 min · Adeel Ilyas

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 documents to be processed are filled in by hand, and scanned images of such forms are used for marker recognition.
November 18, 2015 · 3 min · Adeel Ilyas

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][2] - Ruby Java Bridge gem to deal with Optical Character & Marker Recognition Document.
September 22, 2015 · 3 min · Masood Anwer

C# OCR API - Add User Defined Recognition Blocks and Auto-Detect Text Blocks

We are pleased to announce the monthly release of Aspose.OCR for .NET, version 2.0.0. Our team has been hard at work bringing many useful improvements to this edition of the Aspose.OCR API. You can start exploring the newly added features & enhancements immediately, but before you head to the download section, here is a look at just a few of the biggest features in this month’s release. For a full list of bug fixes and improvements please refer to the download pages in the link above.
June 28, 2014 · 3 min · Babar Raza

Support for Optical Mark Recognition (OMR) with Aspose.OCR for Java 1.7.0

We are pleased to announce the release of Aspose.OCR for Java 1.7.0. In this release we have introduced Optical Mark Recognition (OMR). The Aspose.OMR package can be used to recognize different marked elements in a scanned image. Recognition is processed based on a template that contains graphical mapping of the elements to be recognized from the scanned images. Programmers can now load templates and images, and extract data based on these.
January 19, 2014 · 2 min · Babar Raza

Improved Garbage Element Recognition and New Page Notifier in Aspose.OCR for .NET 1.5.0

We are pleased to announce the release of Aspose.OCR for .NET 1.5.0. In this release we have introduced some improvements and bug fixes along with a new feature. It includes improvement in garbage element detection to increase the recognition accuracy. Rotation and flip parameters are exposed in the public API; the default value is none. Users can specify these parameters to improve recognition speed and accuracy as well. This release also fixed an issue with recognition notification as well as other issues.
April 4, 2013 · 1 min · Tilal Ahmad

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.
November 15, 2012 · 1 min · Tilal Ahmad

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 32pt +/- 20% sizes of the supported font families.
October 19, 2012 · 1 min · Tilal Ahmad

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.
January 16, 2012 · 1 min · Muhammad Ijaz

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.
July 5, 2011 · 2 min · Caroline Von Schmalensee