Biometric technologies have gained a remarkable impetus in high security applications. Various biometric modalities are widely being used these days. The need for unobtrusive biometric recognition can be fulfilled through Face recognition which is the most natural and non intrusive authentication system. However the vulnerability to changes owing to variations in face due to various factors like pose, illumination, ageing, emotions, expressions etc make it necessary to have robust face recognition systems. Various statistical models have been developed so far with varying degree of accuracy and efficiency. This paper discusses a new approach to utilize Eigen face and Fisher face methodology by using medoid instead of mean as a statistic in calculating the Eigen faces and Fisher faces. The method not only requires lesser training but also demonstrates better time efficiency and performance compared to the conventional method of using mean.