Reflection Analysis for Face Morphing Attack Detection
Clemens Seibold, Anna Hilsmann, Peter Eisert

TL;DR
This paper proposes a novel face morphing attack detection method by analyzing inconsistencies in facial illumination and specular highlights, improving the ability to identify fraudulent morphs in biometric systems.
Contribution
It introduces a new approach that examines illumination consistency and specular highlights to detect face morphing attacks, addressing limitations of existing methods.
Findings
Effective detection of morphing attacks through highlight analysis
Inconsistencies in reflections indicate morphing presence
Method improves robustness against different morphing scenarios
Abstract
A facial morph is a synthetically created image of a face that looks similar to two different individuals and can even trick biometric facial recognition systems into recognizing both individuals. This attack is known as face morphing attack. The process of creating such a facial morph is well documented and a lot of tutorials and software to create them are freely available. Therefore, it is mandatory to be able to detect this kind of fraud to ensure the integrity of the face as reliable biometric feature. In this work, we study the effects of face morphing on the physically correctness of the illumination. We estimate the direction to the light sources based on specular highlights in the eyes and use them to generate a synthetic map for highlights on the skin. This map is compared with the highlights in the image that is suspected to be a fraud. Morphing faces with different…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
