Face and Palmprint Multi-Modal Biometric Recognition Based on Feature Level Fusion

Nowadays security becomes a most important issue regarding a spoof attack. So, multimodal biometrics technology has attracted substantial interest for its highest user acceptance, high security, high accuracy, low spoof attack and high recognition performance in biometric recognition system. This multimodal biometrics system introduces recognition of person from two things i.e. face & palm print. Principal Component Analysis (PCA) algorithm is used for reduction of dimension & extraction of features in terms of eigenvalues & eigenvectors. Feature level fusion technique used to fuse the results of face & palm prints and then gives the output as per neural network classifier which gives the correct information about genuine or imposter identity.