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Tesseract is an optical character recognition engine for various operating systems. [5] It is free software, released under the Apache License. [1] [6] [7] Originally developed by Hewlett-Packard as proprietary software in the 1980s, it was released as open source in 2005 and development was sponsored by Google in 2006.
This comparison of optical character recognition software includes: OCR engines, that do the actual character identification; Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines
This is a list of free and open-source software packages (), computer software licensed under free software licenses and open-source licenses.Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
CuneiForm '96 OCR release, with the first adaptive recognition algorithms in the world. Adaptive Recognition - a method based on a combination of two types of printed character recognition algorithms: multifont and omnifont. The system generates an internal font for each input document based on well printed characters using a dynamic adjustment ...
Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...
Graffiti is an essentially single-stroke shorthand handwriting recognition system used in PDAs based on the Palm OS. Graffiti was originally written by Palm, Inc. as the recognition system for GEOS -based devices such as HP's OmniGo 100 and 120 or the Magic Cap -line and was available as an alternate recognition system for the Apple Newton ...
The text areas with text lines in the images are first recognized manually or automatically (segmentation). The text lines are then transcribed manually or automatically. [4] Both automatic segmentation and text recognition can be trained using manually created or corrected examples (ground truth). The new models created in this way can be ...
In return, OCRopus was also used for automatic text recognition in Google Book Search. [7] Licensing under an open source license was made right from the start to facilitate collaboration between industrial and academic research. [8] OCRopus has received further funding from the Andrew W. Mellon Foundation and the BMBF. [9]