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Offline handwritten Amharic word recognition
Department of Computer Science, Addis Ababa University, Ethiopia.
Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.ORCID-id: 0000-0002-4929-1262
2011 (engelsk)Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 32, nr 8, s. 1089-1099Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper describes two approaches for Amharic word recognition in unconstrained handwritten text using HMMs. The first approach builds word models from concatenated features of constituent characters and in the second method HMMs of constituent characters are concatenated to form word model. In both cases, the features used for training and recognition are a set of primitive strokes and their spatial relationships. The recognition system does not require segmentation of characters but requires text line detection and extraction of structural features, which is done by making use of direction field tensor. The performance of the recognition system is tested by a dataset of unconstrained handwritten documents collected from various sources, and promising results are obtained. (C) 2011 Elsevier B.V. All rights reserved.

sted, utgiver, år, opplag, sider
Amsterdam: Elsevier, 2011. Vol. 32, nr 8, s. 1089-1099
Emneord [en]
Amharic, Ethiopic script, Handwriting recognition, Word recognition, OCR, HMM
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-14949DOI: 10.1016/j.patrec.2011.02.007ISI: 000290745100002Scopus ID: 2-s2.0-79953057096OAI: oai:DiVA.org:hh-14949DiVA, id: diva2:408370
Tilgjengelig fra: 2011-04-04 Laget: 2011-04-04 Sist oppdatert: 2018-03-23bibliografisk kontrollert

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