Open Science Research Excellence
@article{(International Science Index):,
  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   = {},
  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, Computer, Energetic, Electronic and Communication Engineering},  volume    = {6},
  number    = {6},
  year      = {2012},
  pages     = {593 - 595},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 66, 2012},