for Health Science,

This paper proposed the use of multimodal feature-level fusion to prove the improvement performance of multimodal authentication. Different algorithm used for features extraction, LG for extracting FKP features, LPQ for iris and Palmprint features extraction, and PCA for extracting face features. Results brought to light that the multimodal authentication process gained higher performance than single modality. The biometric performance using feature-level fusions under “Z-score”, “Tanh”, “Median”, and Min-Max normalization has been demonstrated in this paper