@article{(Open Science Index):https://publications.waset.org/pdf/9030,
	  title     = {Finger Vein Recognition using PCA-based Methods},
	  author    = {Sepehr Damavandinejadmonfared and  Ali Khalili Mobarakeh and Mohsen Pashna and  and  Jiangping Gou
Sayedmehran Mirsafaie Rizi and  Saba Nazari and  Shadi Mahmoodi Khaniabadi and  Mohamad Ali Bagheri
						
},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper a novel algorithm is proposed to merit
the accuracy of finger vein recognition. The performances of
Principal Component Analysis (PCA), Kernel Principal Component
Analysis (KPCA), and Kernel Entropy Component Analysis (KECA)
in this algorithm are validated and compared with each other in order
to determine which one is the most appropriate one in terms of finger
vein recognition.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {6},
	  number    = {6},
	  year      = {2012},
	  pages     = {593 - 595},
	  ee        = {https://publications.waset.org/pdf/9030},
	  url   	= {https://publications.waset.org/vol/66},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 66, 2012},
	}