Markov Models for Handwriting Recognition

2011
ISBN: 978-1-4471-2187-9
Verlag: Springer

Buch, Englisch, 78 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 149 g

Reihe: SpringerBriefs in Computer Science

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains 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, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden Markov models and 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 reviews proposed solutions in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition.

Zielgruppe

Research

Autoren/Hrsg.

Fink, Gernot A.

Plötz, Thomas

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik

Inhaltsverzeichnis

Introduction.- General Architecture.- Markov Model Concepts: The Essence.- Markov Model Based Handwriting Recognition.- Recognition Systems for Practical Applications.- Discussion.