Face recognition using fuzzy discriminant locality preserving projection

doi:10.3923/itj.2013.4340.4345

CORC > 兰州理工大学 > 兰州理工大学

	Face recognition using fuzzy discriminant locality preserving projection
	Lu, Pengli; Jiang, Xingbin
刊名	Information Technology Journal
	2013
卷号	12 期号:17 页码:4340-4345
关键词	Blending Classification (of information) Laplace transforms Dimensionality reduction Fuzzy k-nearest Locality preserving projections Maximum margin criterions Scatter matrix
ISSN号	18125638
DOI	10.3923/itj.2013.4340.4345
英文摘要	A novel approach, namely Fuzzy Discriminant Locality Preserving Projection (FDLPP), is proposed for dimensionality reduction to improve the performance of Discriminant Locality Preserving Projection (DLPP). FDLPP which is based on Maximum Margin Criterion (MMC), pursues to maximize the difference between the locality preserving between-class scatter and locality preserving within-class scatter instead of the ratio. In FDLPP, fuzzy k-nearest is implemented to obtain correct local distribution information and the pursuit of better classification results. Blending the membership degree into the definition of the Laplacian scatter matrix acquire to fuzzy Laplacian scatter matrix. Experiments on ORL, FERET and Yale face databases show the effectiveness with the change in illumination and viewing directions of the proposed method. © 2013 Asian Network for Scientific Information.
语种	英语
出版者	Asian Network for Scientific Information, 308-Lasani Town, Sargodha Road, Faisalabad, Pakistan
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/113191]
专题	兰州理工大学
作者单位	School of Computer and Communication, Lanzhou University of Technology, 730050, Lanzhou, China
推荐引用方式 GB/T 7714	Lu, Pengli,Jiang, Xingbin. Face recognition using fuzzy discriminant locality preserving projection[J]. Information Technology Journal,2013,12(17):4340-4345.
APA	Lu, Pengli,&Jiang, Xingbin.(2013).Face recognition using fuzzy discriminant locality preserving projection.Information Technology Journal,12(17),4340-4345.
MLA	Lu, Pengli,et al."Face recognition using fuzzy discriminant locality preserving projection".Information Technology Journal 12.17(2013):4340-4345.