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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.
Font rasterization is the process of converting text from a vector description (as found in scalable fonts such as TrueType fonts) to a raster or bitmap description. This often involves some anti-aliasing on screen text to make it smoother and easier to read.
Optical character recognition (OCR) is commonly considered to apply to any recognition technique that reads machine printed text. An example of a traditional OCR use case would be to translate the characters from an image of a printed document, such as a book page, newspaper clipping, or legal contract, into a separate file that could be ...
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 ...
Users can use the program to convert image documents (photos, scans, PDF files) and screen captures into editable file formats, including Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Rich Text Format, HTML, PDF/A, searchable PDF, CSV and txt files. [3] Since Version 11, files can be saved in the DjVu format. Since Version 15, the ...
A 2016 analysis of the accuracy and reliability of the OCR packages Google Docs OCR, Tesseract, ABBYY FineReader, and Transym, employing a dataset including 1227 images from 15 different categories concluded Google Docs OCR and ABBYY to be performing better than others. [22]
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.
The latter one develops the first omni-font OCR software, capable of reading any text document. [5] 2000–2016 OCR software is made available online for free, through products like Adobe Acrobat, WebOCR, and Google Drive. [6] [7]