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Optical character recognition
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==Applications== OCR engines have been developed into software applications specializing in various subjects such as receipts, invoices, checks, and legal billing documents. The software can be used for: * [[Data entry|Entering data]] for business documents, e.g. [[Cheque clearing|checks]], passports, invoices, bank statements and receipts * [[Automatic number-plate recognition]] * Passport recognition and [[information extraction]] in airports * Automatically extracting key information from insurance documents{{citation needed|date=February 2020}} * [[Traffic-sign recognition]]<ref name="Zeng2015">{{cite book|author=Zeng, Qing-An |title=Wireless Communications, Networking and Applications: Proceedings of WCNA 2014|url=https://books.google.com/books?id=vCnUCgAAQBAJ|date= 2015|publisher=Springer|isbn=978-81-322-2580-5}}</ref> * Extracting business card information into a contact list<ref>{{cite web|date=22 July 2014|title=[javascript] Using OCR and Entity Extraction for LinkedIn Company Lookup|url=https://community.havenondemand.com/t5/Blog/javascript-Using-OCR-and-Entity-Extraction-for-LinkedIn-Company/ba-p/460|url-status=dead|archive-url=https://web.archive.org/web/20160417145657/https://community.havenondemand.com/t5/Blog/javascript-Using-OCR-and-Entity-Extraction-for-LinkedIn-Company/ba-p/460|archive-date=April 17, 2016}}</ref> * Creating textual versions of printed documents, e.g. [[book scanning]] for [[Project Gutenberg]] * Making electronic images of printed documents searchable, e.g. [[Google Books]] * Converting handwriting in real-time to control a computer ([[pen computing]]) * Defeating or testing the robustness of [[CAPTCHA]] anti-bot systems, though these are specifically designed to prevent OCR.<ref>{{cite web|url=http://www.andrewt.net/blog/how-to-crack-captchas/ |title=How To Crack Captchas |publisher=andrewt.net |date=2006-06-28 |access-date=2013-06-16}}</ref><ref>{{cite web|url=http://www.cs.sfu.ca/~mori/research/gimpy/ |title=Breaking a Visual CAPTCHA |publisher=Cs.sfu.ca |date=2002-12-10 |access-date=2013-06-16}}</ref><ref>{{cite web|author=Resig, John |url=http://ejohn.org/blog/ocr-and-neural-nets-in-javascript/ |title=John Resig β OCR and Neural Nets in JavaScript |publisher=Ejohn.org |date=2009-01-23 |access-date=2013-06-16}}</ref> * Assistive technology for blind and visually impaired users * Writing instructions for vehicles by identifying CAD images in a database that are appropriate to the vehicle design as it changes in real time * Making scanned documents searchable by converting them to PDFs
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