00000cmm a22000004i 4500 UP-99796217611135119 Buklod 20140301103542.0 m go j cr |n |||auu|a 110906s2011 xxk u | eng d 9781447121886 (eBook) 1447121880 (eBook) (iLib)UPD-00214604129 DLC DML eng DMLUC TA 1640 G84 2012eb Plotz, Thomas. Markov models for handwriting recognition [electronic resource] by Thomas Plotz, Gernot A. Fink. London Springer 2011. 1 online resource (vi, 78 p.) ill. SpringerBriefs in Computer Science 2191-5768 Introduction -- General Architecture -- Markov Model Concepts: The Essence -- Markov Model Based Handwriting Recognition -- Recognition Systems for Practical Applications -- Discussion. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. 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. Electronic reproduction. New York SpringerLink c2011. Available via World Wide Web through SpringerLink. Optical character recognition. Arabic character sets (Data processing). Electronic books. Fink, Gernot A. SpringerLink (Online service). SpringerBriefs in Computer Science 2191-5768 Available for University of the Philippines Diliman via SpringerLink. Click here to access http://dx.doi.org/10.1007/978-1-4471-2188-6 (viewed 01 September 2014) FO Monograph UPD DMLR Electronic Resource