Removing gender signature from fingerprints

The need of sharing fingerprint image data in many emerging applications raises concerns about the protection of privacy. It has become possible to use automated algorithms for inferring soft biometrics from fingerprint images. Even if we cannot uniquely match the person to an existing fingerprint, revealing their age or gender may lead to undesirable consequences. Our research is focused on de-identifying fingerprint images in order to obfuscate soft biometrics. In this paper, we first discuss a general framework for soft biometrics fingerprint de-identification. We implemented the framework to reduce the risk of successful estimation of gender from fingerprint images using ad-hoc image filtering. We evaluate the proposed approach through experiments using a data set of rolled fingerprints collected at West Virginia University. Results show the proposed method is effective in preventing gender estimation from fingerprint images.