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Extended StirTrace benchmarking of biometric and forensic qualities of morphed face images

  • Since its introduction in 2014, the face morphing forgery (FMF) attack has received significant attention from the biometric and media forensic research communities. The attack aims at creating artificially weakened templates which can be successfully matched against multiple persons. If successful, the attack has an immense impact on many biometric authentication scenarios including the application of electronic machine-readable travel document (eMRTD) at automated border control gates. WeSince its introduction in 2014, the face morphing forgery (FMF) attack has received significant attention from the biometric and media forensic research communities. The attack aims at creating artificially weakened templates which can be successfully matched against multiple persons. If successful, the attack has an immense impact on many biometric authentication scenarios including the application of electronic machine-readable travel document (eMRTD) at automated border control gates. We extend the StirTrace framework for benchmarking FMF attacks by adding five issues: a novel three-fold definition for the quality of morphed images, a novel FMF realisation (combined morphing), a post-processing operation to simulate the digital image format used in eMRTD (passport scaling 15 kB), an automated face recognition system (VGG face descriptor) as additional means for biometric quality assessment and two feature spaces for FMF detection (keypoint features and fusion of keypoint and Benford features) as additional means for forensic quality assessment. We show that the impact of StirTrace post-processing operations on the biometric quality of morphed face images is negligible except for two noise operators and passport scaling 15 kB, the impact on the forensic quality depends on the type of post-processing, and the new FMF realisation outperforms the previously considered ones.show moreshow less

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Metadaten
Author:Tom Neubert, Andrey Makrushin, Mario Hildebrandt, Christian Kraetzer, Jana Dittmann
URL:https://onlinelibrary.wiley.com/doi/10.1049/iet-bmt.2017.0147
DOI:https://doi.org/10.1049/iet-bmt.2017.0147
ISSN:2047-4938, 2047-4946
Parent Title (English):IET Biometrics
Publisher:Wiley
Document Type:Article
Language:English
Year of Publishing:2018
Date of Publication (online):2024/02/13
Publishing Institution:Technische Hochschule Brandenburg
Release Date:2024/02/14
Issue:Augabe: 4/ Band: 7
Page Number:8
First Page:325
Last Page:332
Institutes:Fachbereich Informatik und Medien
Licence (German):Creative Commons - CC BY - Namensnennung 4.0
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