Cursive Handwritten Word Recognition by Integrating Multiple Classifiers

Authors:
Kenichi Maruyama;Makoto Kobayashi;Hirobumi Yamada;Yasuaki Nakano
Affiliations:
-;-;-;-
Venue:
DAS '98 Selected Papers from the Third IAPR Workshop on Document Analysis Systems: Theory and Practice
Year:
1998

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Abstract

This paper proposes a method for cursive handwritten word recognition. In the traditional research, many cursive handwritten word recognition systems used a single method for character recognition. In this research, we propose a method integrating multiple character classifier to improve word recognition rate combining the results of them. As a result of the experiment using two classifiers, word recognition rate is improved than from those using a single character classifier.