Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm

doi:10.1142/S021800141956007X

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能感知与计算研究中心

	Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm
	Zeng, Zhigao 1,2; Guan, Lianghua 1,2; Zhu, Wenqiu 1,2; Dong, Jing3 ; Li, Jun 4
刊名	INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
	2019-06-30
卷号	33 期号:7 页码:17
关键词	Support vector machine bacterial foraging optimization parameter optimization face recognition local binary pattern
ISSN号	0218-0014
DOI	10.1142/S021800141956007X
通讯作者	Zhu, Wenqiu(wenqiu_zhu@163.com)
英文摘要	Support vector machine (SVM) is always used for face recognition. However, kernel function selection (kernel selection and its parameters selection) is a key problem for SVMs, and it is difficult. This paper tries to make some contributions to this problem with focus on optimizing the parameters in the selected kernel function. Bacterial foraging optimization algorithm, inspired by the social foraging behavior of Escherichia coli, has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control. Therefore, we proposed to optimize the parameters in SVM by an improved bacterial foraging optimization algorithm (IBFOA). In the improved version of bacterial foraging optimization algorithm, a dynamical elimination-dispersal probability in the elimination-dispersal step and a dynamical step size in the chemotactic step are used to improve the performance of bacterial foraging optimization algorithm. Then the optimized SVM is used for face recognition. Simultaneously, an improved local binary pattern is proposed to extract features of face images in this paper to improve the accuracy rate of face recognition. Numerical results show the advantage of our algorithm over a range of existing algorithms.
资助项目	National key R & D Project of China[2017YFC0821602] ; National Natural Science Foundation of China[61271140] ; National Natural Science Foundation of China[U1536120] ; National Natural Science Foundation of China[U1636201] ; National Natural Science Foundation of China[61772529] ; Open Project Program of the National Laboratory of Pattern Recognition (NLPR)[201700009] ; National Natural Science Foundation of Hunan[2018JJ2098] ; National Natural Science Foundation of Hunan[2018JJ3351] ; National Natural Science Foundation of Hunan[2018JJ4078] ; Scientific Research Fund of Hunan Provincial Education Department, China[15A049] ; Education Department Fund of Hunan Province in China[17C0481] ; Science and Technology Planning Project of Hunan Province in China[2015GK3024] ; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System (Wuhan University of Science and Technology)[znxx2018QN06] ; Provincal Joint Fund of Guizhou[LH20147631]
WOS关键词	SUPPORT VECTOR MACHINE ; CLASSIFICATION
WOS研究方向	Computer Science
语种	英语
出版者	WORLD SCIENTIFIC PUBL CO PTE LTD
WOS记录号	WOS:000470871900013
资助机构	National key R & D Project of China ; National Natural Science Foundation of China ; Open Project Program of the National Laboratory of Pattern Recognition (NLPR) ; National Natural Science Foundation of Hunan ; Scientific Research Fund of Hunan Provincial Education Department, China ; Education Department Fund of Hunan Province in China ; Science and Technology Planning Project of Hunan Province in China ; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System (Wuhan University of Science and Technology) ; Provincal Joint Fund of Guizhou
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/26030]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Zhu, Wenqiu
作者单位	1.Hunan Univ Technol, Coll Comp, Zhuzhou City 412007, Hunan, Peoples R China 2.Intelligent Informat Percept & Proc Technol Hunan, Zhuzhou City 412007, Hunan, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Wuhan Univ Sci & Technol, Wuhan 430065, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Zeng, Zhigao,Guan, Lianghua,Zhu, Wenqiu,et al. Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm[J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE,2019,33(7):17.
APA	Zeng, Zhigao,Guan, Lianghua,Zhu, Wenqiu,Dong, Jing,&Li, Jun.(2019).Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm.INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE,33(7),17.
MLA	Zeng, Zhigao,et al."Face Recognition Based on SVM Optimized by the Improved Bacterial Foraging Optimization Algorithm".INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 33.7(2019):17.