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A Hybrid System for Robust Recognition of Ethiopic Script
Addis Ababa University, Department of Computer Science, Addis Ababa, Ethiopia .
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0002-4929-1262
2007 (English)In: Ninth International Conference on Document Analysis and Recognition: proceedings : Curtiba, Paraná, Brazil, September 23-26, 2007 / [ed] IEEE Computer Society, Los Alamitos, Calif.: IEEE Computer Society, 2007, p. 556-560Conference paper, Published paper (Refereed)
Abstract [en]

In real life, documents contain several font types, styles, and sizes. However, many character recognition systems show good results for specific type of documents and fail to produce satisfactory results for others. Over the past decades, various pattern recognition techniques have been applied with the aim to develop recognition systems insensitive to variations in the characteristics of documents. In this paper, we present a robust recognition system for Ethiopic script using a hybrid of classifiers. The complex structures of Ethiopic characters are structurally and syntactically analyzed, and represented as a pattern of simpler graphical units called primitives. The pattern is used for classification of characters using similarity-based matching and neural network classifier. The classification result is further refined by using template matching. A pair of directional filters is used for creating templates and extracting structural features. The recognition system is tested by real life documents and experimental results are reported.

Place, publisher, year, edition, pages
Los Alamitos, Calif.: IEEE Computer Society, 2007. p. 556-560
Keywords [en]
character recognition, character sets, document image processing, feature extraction, iltering theory, image classification, image matching, natural language processing, neural nets
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2151DOI: 10.1109/ICDAR.2007.4378771ISI: 000252162600112Scopus ID: 2-s2.0-51149094370Local ID: 2082/2546ISBN: 978-0-7695-2822-9 (print)OAI: oai:DiVA.org:hh-2151DiVA, id: diva2:239369
Conference
Ninth International Conference on Document Analysis and Recognition, Curtiba, Paraná, Brazil, September 23-26, 2007
Note

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Available from: 2008-11-20 Created: 2008-11-20 Last updated: 2018-03-23Bibliographically 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