This monograph describes the latest advances in discriminative learning methods for biometric
recognition. Specifically it focuses on three representative categories of methods: sparse
representation-based classification metric learning and discriminative feature representation
together with their applications in palmprint authentication face recognition and
multi-biometrics. The ideas algorithms experimental evaluation and underlying rationales are
also provided for a better understanding of these methods. Lastly it discusses several
promising research directions in the field of discriminative biometric recognition.
