• Jun 01, 2020 News!Papers published in Vol.10, No.2 have all received dois from Crossref.
  • May 15, 2020 News!Papers published in Vol.9, No.1-Vol.10, No.1 have all received dois from Crossref.
  • May 15, 2020 News!IJIEE Vol. 10, No. 2 issue has been published online!   [Click]
General Information
    • ISSN: 2010-3719 (Online)
    • Abbreviated Title: Int. J. Inf. Electron. Eng.
    • Frequency: Quarterly
    • DOI: 10.18178/IJIEE
    • Editor-in-Chief: Prof. Chandratilak De Silva Liyanage
    • Executive Editor: Jennifer Zeng
    • Abstracting/ Indexing : Google Scholar, Electronic Journals Library, Crossref and ProQuest,  INSPEC (IET), EBSCO, CNKI.
    • E-mail ijiee@ejournal.net
Editor-in-chief

 
University of Brunei Darussalam, Brunei Darussalam   
" It is a great honor to serve as the editor-in-chief of IJIEE. I'll work together with the editorial team. Hopefully, The value of IJIEE will be well recognized among the readers in the related field."

IJIEE 2014 Vol.4(5): 331-335 ISSN: 2010-3719
DOI: 10.7763/IJIEE.2014.V4.459

Writer Identification for Offline Handwritten Kanji Characters Using Multiple Features

Ayumu Soma, Kozo Mizutani, and Masayuki Arai
Abstract— This paper presents a study on character features and recognizers used for writer identification of offline handwritten Kanji characters. It is shown that a combination of two global features, two local features, and majority voting as a recognizer is efficient for writer identification. We performed experiments using an offline Kanji character database containing one-hundred Kanji characters, each written by one-hundred writers, and fifty samples of each Kanji character for a given writer. The experimental results show that the identification rate is 7 points higher than the conventional method using a single feature and obtained an identification rate higher than 99% by using three character classes.

Index Terms— Multiple features, offline handwritten Kanji character, recognizer, writer identification.

Ayumu Soma and Masayuki Arai are with Graduate School of Science & Engineering, Teikyo University, 1-1 Toyosatodai, Utsunomiya, Tochigi, Japan (e-mail: 12M105@uccl.teikyo-u.ac.jp, arai@ics.teikyo-u.ac.jp).
Kozo Mizutani is with Teikyo University, Faculty of Science and Engineering, Japan (e-mail: mizutani@uccl.teikyo-u.ac.jp).

[PDF]

Cite: Ayumu Soma, Kozo Mizutani, and Masayuki Arai, " Writer Identification for Offline Handwritten Kanji Characters Using Multiple Features," International Journal of Information and Electronics Engineering vol. 4, no. 5, pp. 331-335, 2014.

Copyright © 2008-2021. International Journal of Information and Electronics Engineering. All rights reserved.
E-mail: ijiee@ejournal.net