Difference between revisions of "Publications:Ethiopic Character Recognition Using Direction Field Tensor"

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|Name=Assabie, Yaregal (Addis Ababa University, Department of Computer Science, Addis Ababa, Ethiopia );Bigun, Josef [josef] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941])
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|Name=Assabie, Yaregal (Addis Ababa University, Department of Computer Science, Addis Ababa, Ethiopia );Bigun, Josef (josef) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), Intelligenta system (IS-lab) (3941))
 
|Title=Ethiopic Character Recognition Using Direction Field Tensor
 
|Title=Ethiopic Character Recognition Using Direction Field Tensor
 
|PublicationType=Conference Paper
 
|PublicationType=Conference Paper

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Title Ethiopic Character Recognition Using Direction Field Tensor
Author Yaregal Assabie and Josef Bigun
Year 2006
PublicationType Conference Paper
Journal
HostPublication he 18th International Conference on Pattern Recognition : proceedings : 20-24 August, 2006, Hong Kong
Conference 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, 20 - 24 August, 2006
DOI http://dx.doi.org/10.1109/ICPR.2006.507
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239341
Abstract Many languages in Ethiopia use a unique alphabet called Ethiopic for writing. However, there is no OCR system developed to date. In an effort to develop automatic recognition of Ethiopic script, a novel system is designed by applying structural and syntactic techniques. The recognition system is developed by extracting primitive structural features and their spatial relationships. A special tree structure is used to represent the spatial relationship of primitive structures. For each character, a unique string pattern is generated from the tree and recognition is achieved by matching the string against a stored knowledge base of the alphabet. To implement the recognition system, we use direction field tensor as a tool for character segmentation, and extraction of structural features and their spatial relationships. Experimental results are reported.