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Ethiopic Character Recognition Using Direction Field Tensor
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).
2006 (English)In: The 18th International Conference on Pattern Recognition: proceedings : 20-24 August, 2006, Hong Kong, Los Alamitos, Calif.: IEEE Computer Society, 2006, 284-287 p.Conference paper, (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Los Alamitos, Calif.: IEEE Computer Society, 2006. 284-287 p.
Series
International Conference on Pattern Recognition. Proceedings, ISSN 1051-4651
Keyword [en]
character recognition, feature extraction, image segmentation, knowledge based systems, natural language interfaces, string matching, tensors
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2123DOI: 10.1109/ICPR.2006.507ISI: 000240705600067Scopus ID: 2-s2.0-34147145904Local ID: 2082/2518ISBN: 0-7695-2521-0 (print)OAI: oai:DiVA.org:hh-2123DiVA: diva2:239341
Conference
18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, 20 - 24 August, 2006
Note

©2006 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: 2008-11-11 Created: 2008-11-11 Last updated: 2017-05-23Bibliographically approved
In thesis
1. Multifont recognition System for Ethiopic Script
Open this publication in new window or tab >>Multifont recognition System for Ethiopic Script
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, we present a general framework for multi-font, multi-size and multi-style Ethiopic character recognition system. We propose structural and syntactic techniques for recognition of Ethiopic characters where the graphically comnplex characters are represented by less complex primitive structures and their spatial interrelationships. For each Ethiopic character, the primitive structures and their spatial interrelationships form a unique set of patterns.

The interrelationships of primitives are represented by a special tree structure which resembles a binary search tree in the sense that it groups child nodes as left and right, and keeps the spatial position of primitives in orderly manner. For a better computational efficiency, the primitive tree is converted into string pattern using in-order traversal, which generates a base of the alphabet that stores possibly occuring string patterns for each character. The recognition of characters is then achieved by matching the generated patterns with each pattern in a stored knowledge base of characters.

Structural features are extracted using direction field tensor, which is also used for character segmentation. In general, the recognition system does not need size normalization, thinning or other preprocessing procedures. The only parameter that needs to be adjusted during the recognition process is the size of Gaussian window which should be chosen optimally in relation to font sizes. We also constructed an Ethiopic Document Image Database (EDIDB) from real life documents and the recognition system is tested with respect to variations in font type, size, style, document skewness and document type. Experimental results are reported.

Place, publisher, year, edition, pages
Göteborg: Department of Signals and Systems, Chalmers University of Technology, 2006. 46 p.
Series
Technical report, 2006:21
Keyword
Ethiopic character recognition, OCR, Multifont recognition, Amharic, Direction fields, Structural and syntactic pattern recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-1978 (URN)2082/2373 (Local ID)2082/2373 (Archive number)2082/2373 (OAI)
Presentation
(English)
Supervisors
Available from: 2008-09-29 Created: 2008-09-29 Last updated: 2013-01-16Bibliographically approved

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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