Person identification using face and fingerprint authentication

A biometric system is generally a pattern recognition system which makes a personal identification by determining the authenticity of a specific physiological or behavioral characteristic indigenous from the user. Unimodel biometric systems perform person recognition based on a single source of biometric information and are affected by problems like noisy sensor data, non-universality and lack of individuality of the chosen biometric trait, absence of an invariant representation for the biometric trait and susceptibility to circumvention. Some of these problems can be alleviated by using multimodal biometric systems that consolidate evidence from multiple biometric sources. In this project a new method of multibiomedical authentication system will be introduced using two types of biometric face and the finger print of the person to be identified. This method is based upon developing new hybrid transform from the combination of multiwavelet transform and wavelet network transform as a feature extractor and a classifier. In this proposed system multi method will be used to reach the best solution.