Score level fusion of iris and Finger knuckle print

Multimodal biometrics is an evolving technology in the fields of security. Biometrics system reduces the effort of remember a memorable password. Multimodal biometrics system uses two or more traits for efficient recognition. In this paper, a novel idea is proposed by combining IRIS and Finger knuckle print for recognition. The texture pattern present in IRIS and Finger Knuckle print are distinct when combining both the patterns will become highly distinctive. The two traits were captured using sensors and the features were extracted using Haar Wavelet for IRIS and Linear Discriminant Analysis for Finger Knuckle Print. Both the extracted features were fused at score level. The experimental results has been observed in terms of False Acceptance Rate, False Rejection Rate, Genuine Acceptance Rate and Total Error Rate.