Face recognition based on WT, FastICA and RBF neural network

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	Face recognition based on WT, FastICA and RBF neural network
	Li, Ming; Wu, Fuwen; Liu, Xueyan
	2007
页码	3-+
英文摘要	Face is a complex multidimensional visual model and it is difficult to develop a computational model for recognition. A novel approach is presented to face recognition in this paper, which uses wavelet transform (WT), fast independent component analysis (FastICA) and radial basis function (RBF) neural networks. Firstly, low frequency subband images are extracted from original face image by 2D wavelet transform. Secondly, for reducing computational cost and converges difficultly, improved FastICA is applied to extract features from the low frequency subband image. Then, the extracted features are classified through RBF neural networks. Lastly, the proposed algorithm is tested on the ORL face database and result shows that it has good performance both in terms of recognition accuracy and robustness.
会议录	ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS
会议录出版者	IEEE COMPUTER SOC
会议录出版地	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
语种	英语
资助项目	Foundation of Science Research of Gansu Education Office[0603-10]
WOS研究方向	Computer Science ; Mathematical & Computational Biology ; Imaging Science & Photographic Technology
WOS记录号	WOS:000250427200001
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/38166]
专题	兰州理工大学
通讯作者	Li, Ming
作者单位	Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Li, Ming,Wu, Fuwen,Liu, Xueyan. Face recognition based on WT, FastICA and RBF neural network[C]. 见:.