SOCIFS feature selection framework for handwritten authorship

Draman @ Muda, Azah Kamilah and Choo, Yun Huoy and Draman @ Muda, Noor Azilah (2013) SOCIFS feature selection framework for handwritten authorship. International Journal of Hybrid Intelligent Systems. pp. 83-91. ISSN 1875-8819

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Abstract

The uniqueness of shape and style of handwriting can be used to identify the significant features in confirming the author of writing. This paper is meant to propose a novel feature selection framework for Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS), by exploring existing feature selection frameworks, and compare the performance of proposed feature selection framework against various feature selection methods in Writer Identification in order to find the most significant features. The promising applicability of the proposed framework has been demonstrated in the result and worth to receive further exploration in identifying the handwritten authorship.

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Department of Software Engineeering
Depositing User:	Azah Kamilah Muda
Date Deposited:	25 Mar 2014 07:44
Last Modified:	23 May 2023 11:36
URI:	http://eprints.utem.edu.my/id/eprint/11925
Statistic Details:	View Download Statistic

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