scispace - formally typeset
C

Christian Rathgeb

Researcher at Darmstadt University of Applied Sciences

Publications -  230
Citations -  5215

Christian Rathgeb is an academic researcher from Darmstadt University of Applied Sciences. The author has contributed to research in topics: Biometrics & Iris recognition. The author has an hindex of 33, co-authored 188 publications receiving 3837 citations. Previous affiliations of Christian Rathgeb include University of Salzburg.

Papers
More filters
Journal ArticleDOI

A survey on biometric cryptosystems and cancelable biometrics

TL;DR: A comprehensive survey of biometric cryptosystems and cancelable biometrics is presented and state-of-the-art approaches are reviewed based on which an in-depth discussion and an outlook to future prospects are given.
Journal ArticleDOI

Face Recognition Systems Under Morphing Attacks: A Survey

TL;DR: A conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications, and technical considerations and tradeoffs of the surveyed methods are discussed.
Journal ArticleDOI

General Framework to Evaluate Unlinkability in Biometric Template Protection Systems

TL;DR: This paper proposes a new general framework for the evaluation of biometric templates’ unlinkability and applies it to assess the un linkability of the four state-of-the-art techniques for biometric template protection: biometric salting, bloom filters, homomorphic encryption, and block re-mapping.
Journal ArticleDOI

Demographic Bias in Biometrics: A Survey on an Emerging Challenge

TL;DR: The main contributions of this article are an overview of the topic of algorithmic bias in the context of biometrics, a comprehensive survey of the existing literature on biometric bias estimation and mitigation, and a discussion of the pertinent technical and social matters.
Proceedings ArticleDOI

Alignment-free cancelable iris biometric templates based on adaptive bloom filters

TL;DR: In the presented work alignment-free cancelable iris biometrics based on adaptive Bloom filters are proposed and it is demonstrated that the proposed system maintains biometric performance for diverse iris recognition algorithms, protecting biometric templates at high security levels.