Author(s)

E. Sujatha¹, A. Chilambuchelvan²

¹Department of Information Technology, Kings Engineering College, Chennai, India.
²Department of Computer Science and Engineering, R.M.D. Engineering College, Chennai, India.

A multimodal biometric system is applied to recognize individuals for authentication using neural networks. In this paper multimodal biometric algorithm is designed by integrating iris, finger vein, palm print and face biometric traits. Normalized score level fusion approach is applied and optimized, encoded for matching decision. It is a multilevel wavelet, phase based fusion algorithm. This robust multimodal biometric algorithm increases the security level, accuracy, reduces memory size and equal error rate and eliminates unimodal biometric algorithm vulnerabilities.

Multimodal Biometrics, Score Level Fusion Approach, Neural Network, Optimization

Sujatha, E. and Chilambuchelvan, A. (2016) Neural Network Based Normalized Fusion Approaches for Optimized Multimodal Biometric Authentication Algorithm. Circuits and Systems, 7, 1199-1206. doi: 10.4236/cs.2016.78103.