PSO and Computationally Inexpensive Sequential Forward Floating Selection in Acquiring Significant Features for Handwritten Authorship

Muda, A. K. and Yun-Huoy, C. and Muda, N. A. (2011) PSO and Computationally Inexpensive Sequential Forward Floating Selection in Acquiring Significant Features for Handwritten Authorship. In: International Conference on Hybrid Intelligent Systems 2011, 5 - 8 Dec, 2011, Melaka, Malaysia.

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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. Acquiring these significant features leads to an important research in Writer Identification domain. This paper is meant to explore the usage of feature selection in Writer Identification in order to find the most significant features. This paper proposes a hybrid feature selection method of Particle Swarm Optimization and Computationally Inexpensive Sequential Forward Floating Selection for Writer Identification. The promising applicability of the proposed method has been demonstrated and worth to receive further exploration in identifying the handwritten authorship.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Department of Software Engineeering
Depositing User:	Azah Kamilah Muda
Date Deposited:	09 Dec 2011 12:40
Last Modified:	28 May 2015 02:17
URI:	http://eprints.utem.edu.my/id/eprint/247
Statistic Details:	View Download Statistic

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