Biometric Authentication: A Machine Learning Approach

2.4. Adaptive Classifiers

If individual patterns are available, one can build a statistical model for each class of person. A common approach is to model each class by a normal density so that the system estimates the corresponding mean feature vector and covariance matrix for each person. Using a prior distribution of the individuals in the database, the classification task is completed by computing the Bayesian a posteriori probability of each person, conditioned on the observations of the query. If log probability is computed, the classification process can be considered a nearest-neighbor search using the Mahalanobis distance metric.

There are other statistical approaches to pattern classification. First, the K-nearest-neighbor algorithm ...