A measure of information gained through biometric systems

作者：Takahashi Kenta^*; Murakami Takao

来源：Image and Vision Computing, 2014, 32(12): 1194-1203.

DOI：10.1016/j.imavis.2013.12.010

• Biometrics
• Entropy
• Mutual information
• Relative entropy
• Divergence

We propose a measure of information gained through biometric matching systems. Firstly, we discuss how the information about the identity of a person is derived from biometric samples through a biometric system, and define the "biometric system entropy" or BSE based on mutual information. We present several theoretical properties and interpretations of the BSE, and show how to design a biometric system which maximizes the BSE. Then we prove that the BSE can be approximated asymptotically by the relative entropy D(f(G)(x)parallel to f(I)(x)) where f(G)(x) and f(I)(x) are probability mass functions of matching scores between samples from individuals and among population. We also discuss how to evaluate the BSE of a biometric system and show experimental evaluation of the BSE of face, fingerprint and multimodal biometric systems.

• 出版日期2014-12