Abstract
This paper proposes a methodf or cursive handwritten word recognition. In the traditional research, many cursive handwritten word recognition systems useda single methodfor character recognition. In this research, we propose a methodi ntegrating multiple character classifier to improve wordre cognition rate combining the results of them. As a result of the experiment using two classifiers, wordre cognition rate is improvedt han from those using a single character classifier.
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© 1999 Springer-Verlag Berlin Heidelberg
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Maruyama, K., Kobayashi, M., Nakano, Y., Yamada, H. (1999). Cursive Handwritten Word Recognition by Integrating Multiple Classifiers. In: Lee, SW., Nakano, Y. (eds) Document Analysis Systems: Theory and Practice. DAS 1998. Lecture Notes in Computer Science, vol 1655. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48172-9_12
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DOI: https://doi.org/10.1007/3-540-48172-9_12
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