On-line handwriting recognition with parallelized machine learning algorithms

Authors:
Sebastian Bothe;Thomas Gärtner;Stefan Wrobel
Affiliations:
Department of Computer Science III, University of Bonn, Germany and Fraunhofer Institut für Intelligente Analyse-und Informationssysteme IAIS, Sankt Augustin;Department of Computer Science III, University of Bonn, Germany and Fraunhofer Institut für Intelligente Analyse-und Informationssysteme IAIS, Sankt Augustin;Department of Computer Science III, University of Bonn, Germany and Fraunhofer Institut für Intelligente Analyse-und Informationssysteme IAIS, Sankt Augustin
Venue:
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Year:
2010

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Abstract

The availability of mobile devices without a keypad like Apple's iPad and iPhone grows continuously and the demand for sophisticated input methods with them. In this paper we present classifiers for on-line handwriting recognition based on SVM and kNN algorithms and provide a comparison of the different classifiers using the freely available handwriting corpus UjiPenchars2.We further investigate how their performance can be improved by parallelization and how these improvements can be utilized on a mobile device.