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Offline Handwritten Amharic Word Recognition Using HMMs
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-4929-1262
2009 (English)In: Proceedings SSBA '09: Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 / [ed] Josef Bigun & Antanas Verikas, Halmstad: Halmstad University , 2009, p. 89-92Chapter in book (Other academic)
Abstract [en]

This paper describes two appraches 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 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 DEHR dataset of unconstrained handwritten documents collected from various sources.

Place, publisher, year, edition, pages
Halmstad: Halmstad University , 2009. p. 89-92
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hh:diva-25837ISBN: 978-91-633-3924-0 OAI: oai:DiVA.org:hh-25837DiVA, id: diva2:728445
Available from: 2014-06-24 Created: 2014-06-24 Last updated: 2018-03-22Bibliographically approved

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Assabie, YaregalBigun, Josef

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CiteExportLink to record
Permanent link

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