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Offline grammar-based recognition of handwritten sentences

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BORIS DOI
10.7892/boris.18491
Publisher DOI
10.1109/TPAMI.2006.103
PubMed ID
16640266
Description
This paper proposes a sequential coupling of a Hidden Markov Model (HMM) recognizer for offline handwritten English sentences with a probabilistic bottom-up chart parser using Stochastic Context-Free Grammars (SCFG) extracted from a text corpus. Based on extensive experiments, we conclude that syntax analysis helps to improve recognition rates significantly.
Date of Publication
2006
Publication Type
Article
Subject(s)
000 Computer science, knowledge & systems
500 Science > 510 Mathematics
Keyword(s)
Optical character recognition
•
handwriting analysis
•
natural language parsing and understanding
Language(s)
en
Contributor(s)
Zimmermann, Matthias
Chappelier, Jean-Cédric
Bunke, Horst
Institut für Informatik und angewandte Mathematik (IAM)
Additional Credits
Institut für Informatik und angewandte Mathematik (IAM)
Series
IEEE transactions on mobile computing
Publisher
IEEE Computer Society
ISSN
1536-1233
Access(Rights)
open.access
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