In many real-life usages, single modal biometric systems repeatedly face significant restrictions due to sensitivity to noise, data quality, non-universality, and other factors. However, single traits alone may not be able to meet the increasing demand of high accuracy in today's biometric system. Multi-biometric systems pursue to improve some of these problems by providing multiple pieces of evidence of the same identity. This paper presents an effective fusion scheme that combines the information to investigate whether the integration of palmprint and face biometric can achieve performance that may not be possible using a single biometric technology. In this paper, multimodal authentication system is classified into image acquisition, preprocessing, feature extraction, feature fusion and matching.