Yakshita Jain, Mamta Juneja
Multimodal biometric systems are being adopted as the most effective solution for security breaches these days as they are more reliable and accurate than unimodal systems. These are the pattern recognition systems which are used for identification/verification of the person using their physical or behavioral traits. Background removal for extracting palm print image from an unconstrained background is done using FCM (fuzzy c-mean) technique. Texture feature extraction of both iris and palm print is done using Ridge Energy Detection (RED) algorithm. Score level fusion is used for combining the two modalities and Hamming Distance is applied for generating matching scores for both the traits. The combination of iris and palm print is a very powerful biometric trait due to the individual strengths and uniqueness of both the traits. The proposed work resulted in a Genuine Acceptance Rate (GAR) of 100% at a very low False Acceptance Rate (FAR) of 0.007 only. The Equal Error Rate (EER) value calculated is found to be 0.005. The values are obtained by testing the algorithm on three datasets i.e. Iris Image Dataset provided by IIT Delhi and two for palm print i.e. Palmprint database provided by COEP, touchless palmprint dataset provided by IIT Delhi.
Multimodal Biometrics; security; Iris; Palm print; Background extraction; FCM; Ridge Energy Detection.