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.
[1] A. K. Jain, A. Ross, and S. Prabhakar, "An Introduction to Biometric
Recognition," IEEE Transactions on Circuits and Systems, vol. 14, no.
1, pp. 4-20, 2004.
[2] C. Vision, "A Comparison of Face Recognition Methods Final Project
Report A Combined Project for," Artificial Intelligence, 2003.
[3] S.-hung Lin and D. Ph, "An Introduction to Face Recognition
Technology," Pattern Recognition, no. 1995, pp. 1-7, 1997.
[4] K. I. Kim, K. Jung, and H. J. Kim, "Principal Component Analysis,"
Signal Processing, vol. 9, no. 2, pp. 40-42, 2002.
[5] P. Hu and A.-ping Yang, "Indefinite Kernel Entropy Component
Analysis," Science And Technology, no. 3, pp. 0-3, 2010.
[6] R. Jenssen, "Kernel entropy component analysis.," IEEE transactions on
pattern analysis and machine intelligence, vol. 32, no. 5, pp. 847-60,
May 2010.
[7] S. Damavandinejadmonfared, W. H. Al-arashi, and S. A. Suandi, "Pose
Invariant Face Recognition for Video Surveillance System Using Kernel
Principle Component Analysis," Engineering, pp. 3-7.
[1] A. K. Jain, A. Ross, and S. Prabhakar, "An Introduction to Biometric
Recognition," IEEE Transactions on Circuits and Systems, vol. 14, no.
1, pp. 4-20, 2004.
[2] C. Vision, "A Comparison of Face Recognition Methods Final Project
Report A Combined Project for," Artificial Intelligence, 2003.
[3] S.-hung Lin and D. Ph, "An Introduction to Face Recognition
Technology," Pattern Recognition, no. 1995, pp. 1-7, 1997.
[4] K. I. Kim, K. Jung, and H. J. Kim, "Principal Component Analysis,"
Signal Processing, vol. 9, no. 2, pp. 40-42, 2002.
[5] P. Hu and A.-ping Yang, "Indefinite Kernel Entropy Component
Analysis," Science And Technology, no. 3, pp. 0-3, 2010.
[6] R. Jenssen, "Kernel entropy component analysis.," IEEE transactions on
pattern analysis and machine intelligence, vol. 32, no. 5, pp. 847-60,
May 2010.
[7] S. Damavandinejadmonfared, W. H. Al-arashi, and S. A. Suandi, "Pose
Invariant Face Recognition for Video Surveillance System Using Kernel
Principle Component Analysis," Engineering, pp. 3-7.
@article{"International Journal of Electrical, Electronic and Communication Sciences:58102", 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", title = "Finger Vein Recognition using PCA-based Methods", 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.", keywords = "Biometrics, finger vein recognition, PrincipalComponent Analysis (PCA), Kernel Principal Component Analysis(KPCA), Kernel Entropy Component Analysis (KPCA).", volume = "6", number = "6", pages = "566-3", }