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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 ...
OCRopus is a free document analysis and optical character recognition (OCR) system released under the Apache License v2.0 with a very modular design using command-line interfaces. OCRopus is developed under the lead of Thomas Breuel from the German Research Centre for Artificial Intelligence in Kaiserslautern, Germany and was sponsored by Google.
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.
Ocrad is an optical character recognition program and part of the GNU Project. It is free software licensed under the GNU GPL. Based on a feature extraction method, it reads images in portable pixmap formats known as Portable anymap and produces text in byte (8-bit) or UTF-8 formats. Also included is a layout analyser, able to separate the ...
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
GOCR (or JOCR) is a free optical character recognition program, initially written by Jörg Schulenburg. It can be used to convert or scan image files ( portable pixmap or PCX ) into text files . [ 1 ]
CuneiForm Cognitive OpenOCR is a freely distributed open-source OCR system developed by Russian software company Cognitive Technologies. CuneiForm OCR was developed by Cognitive Technologies as a commercial product in 1993. The system came with the most popular models of scanners, MFPs and software in Russia and the rest of the world: Corel ...
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 ...
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