Accuracy performance analysis of multimodal biometrics

Since biometrics may be used to ensure that a person accessing information is authorized to do so, interest in biometrics for information assurance has increased recently. New biometric applications are constantly being announced while at the same time new spoofing technology is being developed to defeat them. One approach to overcoming the problem of spoofing is the use of multimodal biometric fusion. Most current research is focused on overcoming the deficiencies of a single biometric trait or reducing the false acceptance rate, both without any emphasis on the false rejection rate. Multimodal biometric fusion combines measurements from different biometric traits to enhance the strengths and diminish the weaknesses of the individual measurements. We investigate two types of errors associated with biometrics. The accuracy is analyzed for multimodal biometric systems utilizing two commonly used fusion rules. The purpose of the study is to provide a theoretical evaluation for the false acceptance and the false rejection rates to improve the accuracy as well as the convenience of biometric applications.