Principal Component Analysis-Linear Discriminant Analysis Feature Extractor for Pattern Recognition
Robustness of embedded biometric systems is of prime importance with the emergence of fourth generation communication devices and advancement in security systems This paper presents the realization of such technologies which demands reliable and error-free biometric identity verification systems. High dimensional patterns are not permitted due to eigen-decomposition in high dimensional image space and degeneration of scattering matrices in small size sample. Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors. Results show good pattern by multimodal biometric system proposed in this paper. This paper is aimed at investigating a biometric identity system using Principal Component Analysis and Lindear Discriminant Analysis with K-Nearest Neighbor and implementing such system in real-time using SignalWAVE.
Keywords: Principal Component Analysis, Linear Discriminant Analysis, Nearest Neighbour, Pattern Recognition
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ABOUT THE AUTHORS
Aamir Khan
Aamir KHAN has received M.Sc. degree in Electronic Communications and Computer Engineering from University of Nottingham Malaysia Campus in 2011. He is working at CIIT Wah Campus as lecturer in Electrical Engineering Department. Research interests include embedded systems, intelligent systems and optical communications.
Hasan Farooq
Hasan FAROOQ has received his degree BSc. Degree in Electrical Engineering from University of Engineering and Technology Lahore Pakistan in 2009.s Electrical Engineering Department. He is working as research assistant at CIIT Wah Campus in it Research interests include optical communications, sensor and cognitive networks.
Aamir Khan
Aamir KHAN has received M.Sc. degree in Electronic Communications and Computer Engineering from University of Nottingham Malaysia Campus in 2011. He is working at CIIT Wah Campus as lecturer in Electrical Engineering Department. Research interests include embedded systems, intelligent systems and optical communications.
Hasan Farooq
Hasan FAROOQ has received his degree BSc. Degree in Electrical Engineering from University of Engineering and Technology Lahore Pakistan in 2009.s Electrical Engineering Department. He is working as research assistant at CIIT Wah Campus in it Research interests include optical communications, sensor and cognitive networks.
