OCR for ancient Greek: Difference between revisions

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(definition and request for more examples)
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==Tools and advice for the Optical Character Recognition (OCR) of Ancient Greek==
==Definitions==
 
'''Optical Character Recognition''' or '''OCR''' is the process of using software to reading analogue, printed texts (or raster images of such text) and interpret it as character data, usually using probabilistic pattern-recognition methods. It is related to, but more usually more straightforward than, [[Handwritten Text-Recognition]] (HTR). OCR is relatively easy to perform on modern printed text, but struggles significantly more with: older print and non-standrd fonts; less-common languages with complex diacritical systems; historical language not normally of interest to the AI and intelligence communities who invest a lot in text analysis applications. Ancient Greek is at the intersection of all these difficulties, and has traditionally been among the most difficult printed languages to OCR. The [[TLG]], for example, has compiled hundreds ofmillions of words of Greek literature through outsourced manual keying, rather than even attempting OCR.
 
However, there have recently been several more successful attempts at applying OCR to Ancient Greek, especially involving shared training sets and machine learning approaches. Please add more recent examples and discussion below.
 
==Projects==
 
* Million Books Project
* Perseus Digital Library
* First Thousand Years of Greek
* Open Greek and Latin
[[Lace: Greek OCR]]
 
==Tools, recommendations and policies==


* [http://ancientgreekocr.org Ancient Greek OCR] provides downloads and instructions for OCR using the [http://code.google.com/p/tesseract-ocr Tesseract] engine. Works on Windows, Linux, OSX & Android.
* [http://ancientgreekocr.org Ancient Greek OCR] provides downloads and instructions for OCR using the [http://code.google.com/p/tesseract-ocr Tesseract] engine. Works on Windows, Linux, OSX & Android.

Revision as of 11:58, 30 June 2022

Definitions

Optical Character Recognition or OCR is the process of using software to reading analogue, printed texts (or raster images of such text) and interpret it as character data, usually using probabilistic pattern-recognition methods. It is related to, but more usually more straightforward than, Handwritten Text-Recognition (HTR). OCR is relatively easy to perform on modern printed text, but struggles significantly more with: older print and non-standrd fonts; less-common languages with complex diacritical systems; historical language not normally of interest to the AI and intelligence communities who invest a lot in text analysis applications. Ancient Greek is at the intersection of all these difficulties, and has traditionally been among the most difficult printed languages to OCR. The TLG, for example, has compiled hundreds ofmillions of words of Greek literature through outsourced manual keying, rather than even attempting OCR.

However, there have recently been several more successful attempts at applying OCR to Ancient Greek, especially involving shared training sets and machine learning approaches. Please add more recent examples and discussion below.

Projects

  • Million Books Project
  • Perseus Digital Library
  • First Thousand Years of Greek
  • Open Greek and Latin

Lace: Greek OCR

Tools, recommendations and policies

Alternatives

  • AccessTEI is a service for members of the TEI for manual keying of texts which can handle ancient Greek