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Offline handwritten Amharic word recognition
Department of Computer Science, Addis Ababa University, Ethiopia.
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.ORCID iD: 0000-0002-4929-1262
2011 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 32, no 8, p. 1089-1099Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2011. Vol. 32, no 8, p. 1089-1099
Keywords [en]
Amharic, Ethiopic script, Handwriting recognition, Word recognition, OCR, HMM
National Category
Engineering and Technology
Identifiers
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
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2018-03-23Bibliographically approved

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Assabie, YaregalBigun, Josef

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
  • rtf