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Improved Degraded Document Recognition with Hybrid Modeling Techniques and Character N-Grams

9 years 7 months ago
Improved Degraded Document Recognition with Hybrid Modeling Techniques and Character N-Grams
In this paper a robust multifont character recognition system for degraded documents such as photocopy or fax is described. The system is based on Hidden Markov Models (HMMs) using discrete and hybrid modeling techniques, where the latter makes use of an information theory-based neural network. The presented recognition results refer to the SEDAL-database of English documents using no dictionary. It is also demonstrated that the usage of a language model, that consists of character n-grams yields significantly better recognition results. Our resulting system clearly outperforms commercial systems and leads to further error rate reductions compared to previous results reached on this database.
Anja Brakensiek, Daniel Willett, Gerhard Rigoll
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2000
Where ICPR
Authors Anja Brakensiek, Daniel Willett, Gerhard Rigoll
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