Being able to measure the information content of biometric data has significant importance. However, it is not only difficult to define the biometric information conceptually, but also a challenging estimation problem due to many practical issue such as, different feature representation of different biometric modalities, unknown feature distributions, limited sample size, etc. In this paper, we provided a summary of the several proposed approaches and discuss their merits and shortcomings of these works and focused on techniques which are based on relative entropy. We also introduced a user-specific biometric information measure and evaluated these measures using iris biometric. We explored the effect of the biometric sample quality on the biometric information measurements using different subsets of the iris data with different quality levels. We also investigated the effect of binarization/encoding phase in the iris recognition on the biometric information by comparing our results obtained from image and binary feature domain.