A Comparative Study Of Treebased Structure Methods For Handwriting Identification Springer

Sukor, Nooraziera Akmal and Muda, Azah Kamilah and Draman@Muda, Noor Azilah (2014) A Comparative Study Of Treebased Structure Methods For Handwriting Identification Springer. In: Proceedings Of The First International Conference On Advanced Data And Information Engineering (Daeng-2013) - Springer. Lecture Notes in Electrical Engineering, 285 . Springer, Singapore, pp. 269-276. ISBN 9789814585170

[img] Text
Daeng_Mai.pdf
Restricted to Registered users only

Download (650kB)

Abstract

Handwriting is unique for each individual. Every single word presents the numbers of significant features that can be used for authenticating the author of the writing. The process of identify this significant features is called as feature selection process. Feature selection is an important area in the machine learning, specifically in pattern recognition which is becoming famous among the researchers. Tree-based structure method is one of the feature selection methods which 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. This paper proposes the role of the tree-based structure method performs in Writer Identification. Several methods of the tree-based structure are selected and performed using image dataset from IAM Handwriting Database. The results of each methods of Writer Identification are also analyzed and compared. The most interesting method will be further explored and adapted in future works.

Item Type: Book Section
Uncontrolled Keywords: Feature selection, Writer identification, Treebased,structure, Comparative study
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Information and Communication Technology
Depositing User: Muhammad Afiz Ahmad
Date Deposited: 24 Nov 2017 03:13
Last Modified: 24 Nov 2017 03:13
URI: http://eprints.utem.edu.my/id/eprint/20004
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item