Apart from the goal, OGR and OCR have very little in common. The design and the implementation of our application is somewhat different from the standard OCR design, because we are facing different problems, and different datasets.Well, OGR sounds very much like OCR (which is Optical Character Recognition) because they both share the same goal: the conversion of images of text into characters. In the OGR case, the characters are the glyphs.We are working at a Optical Glyph Recogition (OGR) engine for SignWriting.Dear All,I'd like to take a moment to explain the work of my team (Université Toulouse III - Paul Sabatier, Computer Science Department - "Sapienza" University of Rome) in the latest few years.
We know that there's a huge amount of handwritten SW corpora, scattered around the world, and we believe that they carry an invaluable knowledge, both for the Deaf Community, and for the Research Community. Our goal is to make them digital, to empower their diffusion, and to ensure a long-lasting existence for them.
After a very, very thorough design phase, we are developing the OGR application (and, in confidence, we are about halfway to go) and soon we will release a footage showing our software in action.
To make our OGR stronger, we need to test it with diffrent datasets (SW texts, pages, etc.) we need your help, dear SW list!We need any kind of handwritten SW texts, in any digital image format.
Optionally, we'd like them to be:
- written in columns
- whithout any segmentation (annotation lines, squares, etc.) from one sign to the following oneAnyone can send us some material (even spare pages will DEFINITLEY do) or point us in the right direction?
Thanks in advance for your time, from Rome!
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