Multimodal Biometric for Person Authentication by Fusion

A biometric System which relies only on a single biometric identifier in making a personal identification is often not able to meet the desired performance requirements. Identification based on multiple biometrics represents an emerging trend. We introduce a multimodal biometric system, which integrates face, ear and fingerprint recognition in making a personal identification. This system takes advantage of the capabilities of each individual biometrics. It can be used to overcome some of the limitations of a single biometrics. Preliminary experimental results demonstrate that the identity established by multimodal systems is more reliable than the identity established by a face recognition system alone. In addition, the proposed decision fusion enables the performance improvement by integrating multiple ones with different confidence measures. Further, multibiometric systems provide antispoofing measures by making it difficult for an intruder to spoof multiple biometric traits simultaneously.