TY - JFULL AU - Sepehr Damavandinejadmonfared and Ali Khalili Mobarakeh and Mohsen Pashna and Jiangping Gou Sayedmehran Mirsafaie Rizi and Saba Nazari and Shadi Mahmoodi Khaniabadi and Mohamad Ali Bagheri PY - 2012/7/ TI - Finger Vein Recognition using PCA-based Methods T2 - International Journal of Electrical and Computer Engineering SP - 592 EP - 595 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/9030 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 66, 2012 N2 - 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. ER -