PSO based memetic algorithm for face recognition Gabor filters selection

Jiarui Zhou; Zhen Ji; Linlin Shen; Zexuan Zhu; Siping Chen

doi:10.1109/MC.2011.5953631

PSO based memetic algorithm for face recognition Gabor filters selection

Jiarui Zhou, Zhen Ji, Linlin Shen, Zexuan Zhu, Siping Chen

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

Abstract

A Gabor filters based face recognition algorithm named POMA-Gabor is proposed in this paper. The algorithm uses particular Gabor wavelets in the feature extraction on specific areas of the face image and a particle swarm optimization (PSO) based memetic algorithm (POMA), which combines comprehensive learning particle swarm optimizer (CLPSO) global search and self-adaptive intelligent single particle optimizer (AdpISPO) local search, is introduced to select the Gabor filter parameters. The experimental results demonstrate that POMA obtains better performance than other comparative PSO algorithms. Employing POMA for Gabor filter design, POMA-Gabor is capable of obtaining more representative information and higher recognition rate with less computational time.

Original language	English
Title of host publication	IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011
Subtitle of host publication	2011 IEEE Workshop on Memetic Computing
Pages	9-14
Number of pages	6
DOIs	https://doi.org/10.1109/MC.2011.5953631
Publication status	Published - 2011
Externally published	Yes
Event	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Workshop on Memetic Computing, MC 2011 - Paris, France Duration: 11 Apr 2011 → 15 Apr 2011

Publication series

Name	IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing

Conference

Conference	Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Workshop on Memetic Computing, MC 2011
Country/Territory	France
City	Paris
Period	11/04/11 → 15/04/11

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics

Access to Document

10.1109/MC.2011.5953631

Cite this

Zhou, J., Ji, Z., Shen, L., Zhu, Z., & Chen, S. (2011). PSO based memetic algorithm for face recognition Gabor filters selection. In IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing (pp. 9-14). Article 5953631 (IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing). https://doi.org/10.1109/MC.2011.5953631

Zhou, Jiarui ; Ji, Zhen ; Shen, Linlin et al. / PSO based memetic algorithm for face recognition Gabor filters selection. IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing. 2011. pp. 9-14 (IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing).

@inproceedings{da5d106768114dd08283a47426178a98,

title = "PSO based memetic algorithm for face recognition Gabor filters selection",

abstract = "A Gabor filters based face recognition algorithm named POMA-Gabor is proposed in this paper. The algorithm uses particular Gabor wavelets in the feature extraction on specific areas of the face image and a particle swarm optimization (PSO) based memetic algorithm (POMA), which combines comprehensive learning particle swarm optimizer (CLPSO) global search and self-adaptive intelligent single particle optimizer (AdpISPO) local search, is introduced to select the Gabor filter parameters. The experimental results demonstrate that POMA obtains better performance than other comparative PSO algorithms. Employing POMA for Gabor filter design, POMA-Gabor is capable of obtaining more representative information and higher recognition rate with less computational time.",

author = "Jiarui Zhou and Zhen Ji and Linlin Shen and Zexuan Zhu and Siping Chen",

year = "2011",

doi = "10.1109/MC.2011.5953631",

language = "English",

isbn = "9781612840666",

series = "IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing",

pages = "9--14",

booktitle = "IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011",

note = "Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Workshop on Memetic Computing, MC 2011 ; Conference date: 11-04-2011 Through 15-04-2011",

}

Zhou, J, Ji, Z, Shen, L, Zhu, Z & Chen, S 2011, PSO based memetic algorithm for face recognition Gabor filters selection. in IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing., 5953631, IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing, pp. 9-14, Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Workshop on Memetic Computing, MC 2011, Paris, France, 11/04/11. https://doi.org/10.1109/MC.2011.5953631

PSO based memetic algorithm for face recognition Gabor filters selection. / Zhou, Jiarui; Ji, Zhen; Shen, Linlin et al.
IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing. 2011. p. 9-14 5953631 (IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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AU - Ji, Zhen

AU - Shen, Linlin

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N2 - A Gabor filters based face recognition algorithm named POMA-Gabor is proposed in this paper. The algorithm uses particular Gabor wavelets in the feature extraction on specific areas of the face image and a particle swarm optimization (PSO) based memetic algorithm (POMA), which combines comprehensive learning particle swarm optimizer (CLPSO) global search and self-adaptive intelligent single particle optimizer (AdpISPO) local search, is introduced to select the Gabor filter parameters. The experimental results demonstrate that POMA obtains better performance than other comparative PSO algorithms. Employing POMA for Gabor filter design, POMA-Gabor is capable of obtaining more representative information and higher recognition rate with less computational time.

AB - A Gabor filters based face recognition algorithm named POMA-Gabor is proposed in this paper. The algorithm uses particular Gabor wavelets in the feature extraction on specific areas of the face image and a particle swarm optimization (PSO) based memetic algorithm (POMA), which combines comprehensive learning particle swarm optimizer (CLPSO) global search and self-adaptive intelligent single particle optimizer (AdpISPO) local search, is introduced to select the Gabor filter parameters. The experimental results demonstrate that POMA obtains better performance than other comparative PSO algorithms. Employing POMA for Gabor filter design, POMA-Gabor is capable of obtaining more representative information and higher recognition rate with less computational time.

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DO - 10.1109/MC.2011.5953631

M3 - Conference contribution

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T3 - IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing

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BT - IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011

T2 - Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Workshop on Memetic Computing, MC 2011

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Zhou J, Ji Z, Shen L, Zhu Z, Chen S. PSO based memetic algorithm for face recognition Gabor filters selection. In IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing. 2011. p. 9-14. 5953631. (IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MC 2011: 2011 IEEE Workshop on Memetic Computing). doi: 10.1109/MC.2011.5953631

PSO based memetic algorithm for face recognition Gabor filters selection

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