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HMM-Based Handwritt...
HMM-Based Handwritten Amharic Word Recognition with Feature Concatenation
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- Assabie, Yaregal, 1975- (författare)
- Addis Ababa University, Department of Computer Science, Addis Ababa Ethiopia
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- Bigun, Josef, 1961- (författare)
- Högskolan i Halmstad,Intelligenta system (IS-lab)
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(creator_code:org_t)
- New York : IEEE Press, 2009
- 2009
- Engelska.
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Ingår i: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. - New York : IEEE Press. ; , s. 961-965
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Amharic is the official language of Ethiopia and uses Ethiopic script for writing. In this paper, we present writer-independent HMM-based Amharic word recognition for offline handwritten text. The underlying units of the recognition system are a set of primitive strokes whose combinations form handwritten Ethiopic characters. For each character, possibly occurring sequences of primitive strokes and their spatial relationships, collectively termed as primitive structural features, are stored as feature list. Hidden Markov models for Amharic words are trained with such sequences of structural features of characters constituting words. The recognition phase does not require segmentation of characters but only requires text line detection and extraction of structural features in each text line. Text lines and primitive structural features are extracted by making use of direction field tensor. The performance of the recognition system is tested by a database of unconstrained handwritten documents collected from various sources.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Nyckelord
- TECHNOLOGY
- TEKNIKVETENSKAP
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)