Biometrics has become fashionable in areas that require a high level of security and control. Among all the technologies that exist, face recognition is one of the most used and adapted technologies. In this work, we propose a new fusion of two projection based face recognition algorithms in Discrete wavelet transform domain(DWT).Those two algorithms are Relevance Weighted Linear Discriminant Analysis(RW-LDA) and singular value decomposition (SVD) using the left and right singular vectors. Our experimental work conducted on two well known facial databases indicate that the application of the Min- Max, Z-score normalization schemes followed by a fusion method demonstrates improvement in terms of recognition rate and training time.