A Comparative Study of Tree-based Structure Methods for Handwriting Identification

  • Nooraziera Akmal Binti SukorEmail author
  • Azah Kamilah Muda
  • Noor Azilah Muda
  • Choo Yun Huoy
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 285)


Handwriting Identification is a process to determine the author of the writing and it involves some of process. Classification process is a final stage of Handwriting Identification process where it will analyze the classification accuracy and based on the number of features selected. In this study, classification process was conducted using various tree-based structure methods. Tree-based structure method is one of the classification methods where it is able to generate a compact subset of non-redundant features and hence improves interpretability and generalization. However its focus is still limited especially in Writer Identification domain. Several of tree-based structure selected and performed using image dataset from IAM Handwriting Database. The results also analyze and compared of each methods of Writer Identification. Random Forest Tree classifier gives the best result with the highest percentage of accuracy followed by J48, Random Tree, REP Tree and Decision Stump.


Feature selection Writer identification Tree-based structure Comparative study 


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This work is funded by the Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM).


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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Nooraziera Akmal Binti Sukor
    • 1
    Email author
  • Azah Kamilah Muda
    • 1
  • Noor Azilah Muda
    • 1
  • Choo Yun Huoy
    • 1
  1. 1.Faculty of Information and CommunicationUniversiti Teknikal Malaysia MelakaMelakaMalaysia

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