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One of the most common applications of data capture is extracting information from paper documents and saving it into databases (CMS, ECM, etc.). Basic technologies used for data capture vary by data type:{{Citation needed|date=April 2013}}
* [[Optical character recognition|OCR]] – for printed text recognition<ref>{{cite web |date=22 July 2016 |title=What is Optical Character Recognition (OCR)? |url=http://www.ukdataentry.com/optical-character-recognition/ |access-date=22 July 2016 |website=www.ukdataentry.com}}</ref><ref>{{Cite web|title=What is OCR? - Optical Character Recognition Explained|url=https://aws.amazon.com/what-is/ocr/|access-date=2025-06-27|website=Amazon Web Services}}</ref><ref>{{Cite web|title=OCR - How it works|url=https://pdfguru.com/pdf-ocr|archive-url=https://archive.today/20130411134627/http://www.nicomsoft.com/optical-character-recognition-ocr-how-it-works/|archive-date=
* [[Intelligent character recognition|ICR]] – for hand-printed text recognition<ref>{{Cite web|title=ICR - Glossary |url=https://www.digitizationguidelines.gov/term.php?term=icr|access-date=2025-06-27|website=Federal Agencies Digitization Guidelines Initiative}}</ref>
* [[Optical mark recognition|OMR]] – for marks recognition<ref>Palmer, Roger C. (1989, Sept) The Basics of Automatic Identification [Electronic version]. Canadian Datasystems, 21 (9), 30-33</ref>
* OBR/BCR – for barcode recognition<ref>{{cite news|url=http://searchmanufacturingerp.techtarget.com/definition/bar-code|title=bar code (or barcode)|publisher=TechTarget|date=2009-10-01|access-date=2017-03-09|first=Margaret|last=Rouse|archive-date=
* DLR – for document layer recognition{{Citation needed|date=April 2013}}
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