Markov Models for Handwriting Recognition

Beschreibung:

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. This text reviews proposed solutions in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition. Series: SpringerBriefs in Computer Science. Num Pages: 84 pages, 5 black & white illustrations, biography. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 4. Weight in Grams: 150. . 2011. 2011. Paperback. . . . . Books ship from the US and Ireland. Bestandsnummer des Verkäufers V9781447121879

Diesen Artikel melden

Inhaltsangabe:

Von der hinteren Coverseite:

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.