Comparative analysis of PCA-based and Neural Network based face recognition systems

The continuous growth of insecurity issues around the world has further increased public interest in biometric surveillance systems. Face recognition has proven to be definitive in this area due to its low intrusiveness, accuracy and finesse unlike other biometric systems. This paper presents a comparative analysis of the performance of some selected face recognition systems, namely the PCA, 2DPCA and Artificial Neural Network. The algorithms were implemented and tested exhaustively to evaluate the performance of these algorithms under different face databases in respect to false acceptance rate and false rejection rate.