Handprinted Hiragana recognition using support vector machines

Author

Maruyama, Ken-ichi ; Maruyama, Minoru ; Miyao, Hidetoshi ; Nakano, Yasuaki

Author_Institution

Dept. of Inf. Eng., Shinshu Univ., Nagano, Japan

fYear

2002

fDate

2002

Firstpage

55

Lastpage

60

Abstract

Describes a method to improve the cumulative recognition rates of pattern recognition using a decision directed acyclic graph (DDAG) based on support vector machines (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 construct a DDAG which can incorporate the cumulative recognition rate. As a result of our experiment for handprinted 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 faster than the Max Win Algorithm which is one of the famous recognition methods using support vector machines for a multi-class problem.

Keywords

decision diagrams; directed graphs; handwritten character recognition; learning automata; JEITA-HP; cumulative recognition rates; decision directed acyclic graph; handprinted Hiragana recognition; multi-class problem; pattern recognition; support vector machines; Character generation; Character recognition; Conferences; Kernel; Lagrangian functions; Pattern recognition; Quadratic programming; Support vector machine classification; Support vector machines; Voting;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers in Handwriting Recognition, 2002. Proceedings. Eighth International Workshop on

Print_ISBN

0-7695-1692-0

Type

conf

DOI

10.1109/IWFHR.2002.1030884

Filename

1030884