Optical Character Recognition: Difference between revisions

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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. 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 [http://heml.mta.ca/ Heml Text Mining] project) to “apps” on mobile phones (such as the [https://play.google.com/store/apps/details?id=com.renard.ocr Text Fairy] Android app.).
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. 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 [http://heml.mta.ca/ Heml Text Mining] project) to “apps” on mobile phones (such as the [https://play.google.com/store/apps/details?id=com.renard.ocr Text Fairy] Android app.).


There are several graphical applications (such as [http://sourceforge.net/projects/gimagereader/ gImageReader] and [http://code.google.com/p/lector/ 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 [https://www.dur.ac.uk/nick.white/grctraining/desktop.html guide to setting up Ancient Greek OCR on a desktop PC].
Downloads, simple instructions, and more information can be found at the [http://ancientgreekocr.org/ Ancient Greek OCR website].
 
More information can be found at the [https://www.dur.ac.uk/nick.white/grctraining Ancient Greek Training for Tesseract webpage]. If you have any questions or feedback, please send them to [mailto:nick.white@durham.ac.uk Nick White].

Revision as of 19:10, 5 May 2014

Transforming printed pages of Ancient Greek into fully searchable and editable Unicode text

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. 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.).

Downloads, simple instructions, and more information can be found at the Ancient Greek OCR website.

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