Multibiometric fusion is an active research area for many years. Score normalization is to transform the scores from different matchers to a common domain. In this paper, we give a survey of classical score normalization techniques and recent advances of this research area. The performance of different normalization functions, such as MinMax, Tanh, Zscore, PL, LTL, RHE and FF are evaluated in XM2VTS Benchmark. We evaluated the performance with four different measures of biometric systems such as EER, AUC, GAR(FAR=0.001) and the threshold of EER. The experimental results show that there is no single normalization technique that would perform the best for all multibiometric recognition systems. PL and FF normalization outperform other methods in many applications.