Offline Text-Independent Chinese Writer Identification Using GLDM Features


  • 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.


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


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.


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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