In this paper, multiple algorithm and score-level fusion for enhancing the performance of the face based Biometric Person Authentication System is discussed. Though many algorithms are conferred, several crucial issues are still involved in the face authentication. Most traditional algorithms are based on certain assumptions failing which the system will not give appropriate results. Due to the inherent variations in face with time and space, it is a big challenge to formulate a single algorithm based on the face biometric that works well under all variations. This paper addresses the problem of illumination and pose variations, by using three algorithms for face recognition, Block Independent Component Analysis (B-ICA), Discrete Cosine Transform (DCT) and Kalman Filter and weighted average based score level fusion to improve the results obtained of the system. An intensive analysis of the various algorithms has been performed and the results indicate an increase in accuracy of the proposed system.