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20072025
most citedThe Fuzzy Vault for fingerprints is Vulnerable to Brute Force Attack

54 citations · 104 across the 8 of their papers we have counts for

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cs.CV2025

Deep Learning-based Compression Detection for explainable Face Image Quality Assessment

Laurin Jonientz, Johannes Merkle, Christian Rathgeb +2

The assessment of face image quality is crucial to ensure reliable face recognition. In order to provide data subjects and operators with explainable and actionable feedback regard…

cs.CV2022★ 2 cited

State of the Art of Quality Assessment of Facial Images

Johannes Merkle, Christian Rathgeb, Benjamin Tams +3

The goal of the project "Facial Metrics for EES" is to develop, implement and publish an open source algorithm for the quality assessment of facial images (OFIQ) for face recogniti…

cs.CV2021

Deep Face Fuzzy Vault: Implementation and Performance

Christian Rathgeb, Johannes Merkle, Johanna Scholz +2

Biometric technologies, especially face recognition, have become an essential part of identity management systems worldwide. In deployments of biometrics, secure storage of biometr…

cs.CV2016★ 11 cited

Perfect Fingerprint Orientation Fields by Locally Adaptive Global Models

Carsten Gottschlich, Benjamin Tams, Stephan Huckemann

Fingerprint recognition is widely used for verification and identification in many commercial, governmental and forensic applications. The orientation field (OF) plays an important…

cs.CV2007★ 54 cited

The Fuzzy Vault for fingerprints is Vulnerable to Brute Force Attack

Preda Mihailescu

The \textit{fuzzy vault} approach is one of the best studied and well accepted ideas for binding cryptographic security into biometric authentication. The vault has been implemente…