Optical Character Recognition: Difference between revisions
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{{DISPLAYTITLE:Optical Character Recognition for Ancient Greek}} | {{DISPLAYTITLE:Optical Character Recognition for Ancient Greek}} | ||
== Enabling you to transform printed pages of Ancient Greek into fully searchable and editable Unicode text == | == Enabling you to transform printed pages of Ancient Greek into fully searchable and editable Unicode text == | ||
Revision as of 09:25, 8 July 2013
Enabling you to transform printed pages of Ancient Greek into fully searchable and editable Unicode text
We have developed Optical Character Recognition (OCR) software for Ancient Greek.
We built upon the excellent open source Tesseract OCR engine, “training” it on different Ancient Greek character shapes, wordlists, and some basic grammar. Along the way, we found and fixed several bugs in Tesseract, and significantly improved the project's documentation. We also developed a suite of training tools and OCR testing tools, that have been released under an open source license and have been used by several other people working to improve OCR in different languages.
The end result is a high-quality OCR engine for Ancient Greek, with accuracy generally between 90% and 96% for average quality page scans of old printed volumes, now out of copyright. Because it leverages the Tesseract OCR code, our work can be used in a large variety of settings, from server clusters (as Bruce Robertson is doing with his Heml Text Mining project) to “apps” on mobile phones (such as the Text Fairy Android app.).
There are several graphical applications (such as gImageReader and Lector) that can be set up to use the OCR software on a desktop PC: these are quite straightforward to use once installed and correctly configured. We hope to work to make Ancient Greek OCR on the desktop even more straightforward to use in the future, by automating the tricky installation and configuration steps and providing simple packages for Windows and Mac OS X. For now, we have written a basic guide to setting up Ancient Greek OCR on a desktop PC.
More information can be found at the Ancient Greek Training for Tesseract webpage. If you have any questions or feedback, please send them to Nick White.
