An Enhanced Empirical Method on Choosing the Highest Principal Features and the Number of Hidden Neurons in Principal Component Analysis-Artificial Neural Network Face Recognition Based System

Provided by: International Journal of Computer Applications
Topic: Security
Format: PDF
With fast evolving technology, it is necessary to design an efficient security system which can detect unauthorized access on any system. It's needed to implement an extremely secure, economic and perfect system for face recognition that can protect systems from unauthorized access. So, in this paper, a robust face recognition system approach is proposed for feature extraction using Principal Component Analysis (PCA), and recognition using feed forward back propagation neural network. The proposed approach gave better results in all aspects including recognition rate, training time, elapsed time and mean square error.

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