PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship

Satrya Fajri Pratama; Azah Kamilah Muda; Yun Huoy Choo; Noor Azilah Muda

doi:10.1109/HIS.2011.6122132

PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship

Satrya Fajri Pratama, Azah Kamilah Muda, Yun Huoy Choo, Noor Azilah Muda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011
Pages	358-363
Number of pages	6
DOIs	https://doi.org/10.1109/HIS.2011.6122132
Publication status	Published - 2011
Event	2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 - Malacca, Malaysia Duration: 5 Dec 2011 → 8 Dec 2011

Publication series

Name	Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011

Conference

Conference	2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011
Country/Territory	Malaysia
City	Malacca
Period	5/12/11 → 8/12/11

Keywords

computationally inexpensive
feature selection
particle swarm optimization
significant features
writer identification

Access to Document

10.1109/HIS.2011.6122132

Cite this

Pratama, S. F., Muda, A. K., Choo, Y. H., & Muda, N. A. (2011). PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship. In Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 (pp. 358-363). Article 6122132 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011). https://doi.org/10.1109/HIS.2011.6122132

Pratama, Satrya Fajri ; Muda, Azah Kamilah ; Choo, Yun Huoy et al. / PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship. Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. pp. 358-363 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011).

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title = "PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship",

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.",

keywords = "computationally inexpensive, feature selection, particle swarm optimization, significant features, writer identification",

author = "Pratama, {Satrya Fajri} and Muda, {Azah Kamilah} and Choo, {Yun Huoy} and Muda, {Noor Azilah}",

year = "2011",

doi = "10.1109/HIS.2011.6122132",

language = "English",

isbn = "9781457721502",

series = "Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011",

pages = "358--363",

booktitle = "Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011",

note = "2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011 ; Conference date: 05-12-2011 Through 08-12-2011",

}

Pratama, SF, Muda, AK, Choo, YH & Muda, NA 2011, PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship. in Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011., 6122132, Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011, pp. 358-363, 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011, Malacca, Malaysia, 5/12/11. https://doi.org/10.1109/HIS.2011.6122132

PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship. / Pratama, Satrya Fajri; Muda, Azah Kamilah; Choo, Yun Huoy et al.
Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. p. 358-363 6122132 (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Pratama SF, Muda AK, Choo YH, Muda NA. PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship. In Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011. 2011. p. 358-363. 6122132. (Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems, HIS 2011). doi: 10.1109/HIS.2011.6122132

PSO and computationally inexpensive sequential forward floating selection in acquiring significant features for handwritten authorship

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