Murukesh C., Thanushkodi K., Preethi P., Mohamed F.N. (2015) Multimodal Biometric Authentication System Based on Score-Level Fusion of Palmprint and Finger Vein. In: Suresh L., Dash S., Panigrahi B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 324. Springer, New Delhi
Multimodal biometrics plays a major role in our day-to-day life to meet the requirements with the well-grown population. In this paper, palmprint and finger vein images are fused using normalization scores of the individual traits. Palmprint features extracted from the discrete cosine transform (DCT) are classified by using multi-class linear discriminant analysis (LDA) and self-organizing maps (SOM). Finger vein identification is designed and developed by using repeated line tracking method to extract the patterns. A multimodal biometric authentication system integrates information from multiple biometric sources to compensate for the limitations in performance of each individual biometric system. These systems can significantly improve the recognition performance of a biometric system apart from catalyzing population coverage, impeding spoof attacks, increasing the degrees of freedom, and reducing the failure rates.