Handprinted Hiragana Recognition Using Support Vector Machines

Authors:
Ken-ichi Maruyama;Minoru Maruyama;Hidetoshi Miyao;Yasuaki Nakano
Affiliations:
-;-;-;-
Venue:
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Year:
2002

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Abstract

This paper describes a method to improve the cumulative recognition rates of pattern recognition using Decision Directed Acyclic Graph (DDAG) based on support vectormachines (SVM). Though the original DDAG has high level of performance and its execution speed is fast, it does not consider the so-called cumulative recognition rate. We constructDDAG which can incorporate the cumulative recognition rate. As a result of our experiment for the hand-printed Hiragana characters in JEITA-HP, the cumulative recognition rate is improved and its execution time is almost the same as the original DDAG and 30 times fasterthan Max Win Algorithm which is one of famous recognition methods using support vector machines for a multi-class problem.