Improving Robustness of Biometric Identity Determination with Digital Watermarking

Abstract

The determination of an identity from noisy biometric measurements is a continuing challenge. In many applications, such as identity-based encryption, the identity needs to be known with virtually 100% certainty. The determination of identities with such precision from face images taken under a wide range of natural situations is still an unsolved problem. We propose a digital watermarking based method to aid face recognizers to tackle this problem in applications. In particular, we suggest embedding multiple face dependent watermarks into an image to serve as expert knowledge on the corresponding identities to identity-based schemes. This knowledge could originate, for example, from the tagging of those people on a social network. In our proposal, a single payload consists of a correction vector that can be added to the extracted biometric template to compile a nearly noiseless identity. It also supports the removal of a person from the image. If a particular face is censored, the corresponding identity is also removed. Based on our experiments, our method is robust against JPEG compression, image filtering, and occlusion and enables a reliable determination of an identity without side information.