Performance issues in biometric authentication based on information theoretic concepts: A review

AbstractMany of the performance evaluation techniques for biometric authentication use error probabilities to yield a measure called receiver operating characteristic (ROC). The ROC is based on the Neyman-Pearson hypothesis testing and is obtained by varying a threshold for decision making. This measure is dependent on database partitioning and choice of thresholds. Also, obtaining the probability distributions, and thus the ROC, is computationally complex. Recent approaches based on information theoretic models partially overcome these limitations and also provide insight into the performance of biometric authentication techniques. Measures in line with obtaining Chernoff capacity and with Shannon capacity have been proposed, and are respectively called recognition capacity and constrained capacity. Measures which are largely independent of data size and quality are based on the minimization of false matches between templates and are good indicators of biometrics uniqueness or, equivalently, its random c...