An Efficient Multimodal Biometric Authentication Integrating Fingerprint and Face Features

Biometrics authentication has been used in many applications such as e-commerce, access control etc. In this research, multimodal biometric authentication in light of score level combination of fingerprint and face is proposed. Face and fingerprint is two of the most popular biometric traits and can complement each other for more reliable user authentication. To verify the effectiveness of the proposed method, FERET, SDUMLA-HMT and FVC2002 databases are used in this research. Furthermore, experimental results showed that the proposed fusion based method for fingerprint and face recognition can improve the performance in terms of Equal Error Rate (EER). Eventually, the experimental result shows that our proposed fusion based technique appears to be promising with 7.01~9.13% of EER based on the different datasets.