Offline Text-Independent Chinese Writer Identification Using GLDM Features

Authors

  • Gloria Jennis Tan Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia.
  • Ghazali Sulong Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia. School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
  • Mohd Shafry Mohd Rahim Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia.

Keywords:

Chinese Handwriting Identification, TextIndependent Writer Identification, Writer Recognition, Writer Retrieval,

Abstract

This paper presents a method using retrieval mechanism along with Gray-Level Difference Method (GLDM) feature extraction, an approach based on the textural features which is firstly introduced for off-line, text-independent Chinese writer identification. A widely used performance evaluation database HIT-MW has been used for conducting the experiment. An improvement in the identification rates has been revealed in the experimental evaluations by decreasing the search space using a writer retrieval mechanism prior to identification.

Downloads

Download data is not yet available.

Downloads

Published

2017-10-20

How to Cite

Tan, G. J., Sulong, G., & Mohd Rahim, M. S. (2017). Offline Text-Independent Chinese Writer Identification Using GLDM Features. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-3), 177–184. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2899

Issue

Vol. 9 No. 3-3: Special Issue on Software Engineering I

Section

Articles

License

Copyright (c) 2024 Journal of Telecommunication, Electronic and Computer Engineering

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)