Markov Models for Handwriting Recognition

  • Thomas Plötz
  • Gernot A. Fink

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Thomas Plötz, Gernot A. Fink
    Pages 1-8
  3. Thomas Plötz, Gernot A. Fink
    Pages 9-17
  4. Thomas Plötz, Gernot A. Fink
    Pages 19-26
  5. Thomas Plötz, Gernot A. Fink
    Pages 27-45
  6. Thomas Plötz, Gernot A. Fink
    Pages 47-66
  7. Thomas Plötz, Gernot A. Fink
    Pages 67-75

About this book

Introduction

Since their first inception more than half a century ago, automatic reading systems have evolved substantially, thereby showing impressive performance on machine-printed text. The recognition of handwriting can, however, still be considered an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, so far, no standard procedures for building Markov-model-based recognizers could be established though trends toward unified approaches can be identified.

Markov Models for Handwriting Recognition provides a comprehensive overview of the application of Markov models in the research field of handwriting recognition, covering both the widely used hidden Markov models and the less complex Markov-chain or n-gram models. First, the text introduces the typical architecture of a Markov model-based handwriting recognition system, and familiarizes the reader with the essential theoretical concepts behind Markovian models. Then, the text gives a thorough review of the solutions proposed in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition.

Keywords

Document Analysis Handwriting Recognition Hidden Markov Models Machine Learning Offline Handwriting Recognition Online Handwriting Recognition Pattern Recognition Reading Systems n-Gram Language Models

Authors and affiliations

  • Thomas Plötz
    • 1
  • Gernot A. Fink
    • 2
  1. 1.Culture Lab, School of Computing ScienceNewcastle UniversityNewcastle upon TyneUnited Kingdom
  2. 2.Department of Computer ScienceTechnische Universität DortmundDortmundGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-2188-6
  • Copyright Information Thomas Plötz 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-2187-9
  • Online ISBN 978-1-4471-2188-6
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • About this book