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The program is written in Python and uses the GTK+ library (using PyGTK). [12] It acts as a graphical front-end for other existing tools. For example, it does not make actual character recognition itself, but uses external programs such as an “OCR engine” that is installed on the system.
Asprise OCR is a commercial optical character recognition and barcode recognition SDK library that provides an API to recognize text as well as barcodes from images (in formats like JPEG, PNG, TIFF, PDF, etc.) and output in formats like plain text, XML and searchable PDF. Asprise OCR has been in active development since 1997.
Software development kits that are used to add OCR capabilities to other software (e.g. forms processing applications, document imaging management systems, e-discovery systems, records management solutions)
Supports a range of annotation types. Annotations are stored separately from the unmodified PDF file, or (since version 0.15 with Poppler 0.20) can be saved in the document as standard PDF annotations. Evince: GNU GPL: Yes Yes Default PDF and file viewer for GNOME; replaces GPdf. Supports addition and removal (since v3.14), of basic text note ...
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 ...
hOCR is an open standard of data representation for formatted text obtained from optical character recognition (OCR). The definition encodes text, style, layout information, recognition confidence metrics and other information using Extensible Markup Language (XML) in the form of Hypertext Markup Language (HTML) or XHTML.
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.
One of the most useful application tasks of data capture is collecting information from paper documents and saving it into databases (CMS, ECM, and other systems). There are several types of basic technologies used for data capture according to the data type: [citation needed] OCR – for printed text recognition [3]