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Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines; 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)
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 .
The Text Services Framework is designed to offer advanced language and word processing features to applications. It supports features such as multilingual support, keyboard drivers, handwriting recognition, speech recognition, as well as spell checking and other text and natural language processing functions. It is also downloadable for older ...
Another possibility is the acquisition by means of stylus-operated PDAs. Dynamic recognition is also known as "on-line". Dynamic information for handwriting movement analysis usually consists of the following information: spatial coordinate x(t) spatial coordinate y(t) pressure p(t) azimuth az(t) inclination in(t)
Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices.
CuneiForm Cognitive OpenOCR is a freely distributed open-source Optical character recognition 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 ...
When cursive handwriting is in play, for each word analyzed, the system breaks down the words into a sequence of graphemes, or subparts of letters. These various curves, shapes and lines make up letters and IWR considers these various shape and groupings in order to calculate a confidence value associated with the word in question. [4]
Intelligent word recognition (IWR) can recognize and extract not only printed-handwritten information, cursive handwriting as well. ICR recognizes on the character-level, whereas IWR works with full words or phrases. Capable of capturing unstructured information from every day pages, IWR is said to be more evolved than hand print ICR. [citation ...
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