Toggle Main Menu Toggle Search

Open Access padlockePrints

Markov Models for Handwriting Recognition

Lookup NU author(s): Dr Thomas Ploetz


Full text is not currently available for this publication.


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.

Publication metadata

Author(s): Ploetz T, Fink G

Publication type: Authored Book

Publication status: Published

Series Title: SpringerBriefs in Computer Science

Year: 2011

Number of Pages: 78

Publisher: Springer

Place Published: London, UK

Library holdings: Search Newcastle University Library for this item

ISBN: 9781447121879