Detecting Morphing Attacks through Face Geometry Features

Face-morphing operations allow for the generation of digital faces that simultaneously carry the characteristics of two different subjects. It has been demonstrated that morphed faces strongly challenge face-verification systems, as they typically match two different identities. This poses serious security issues in machine-assisted border control applications and calls for techniques to automatically detect whether morphing operations have been previously applied on passport photos. While many proposed approaches analyze the suspect passport photo only, our work operates in a differential scenario, i.e., when the passport photo is analyzed in conjunction with the probe image of the subject acquired at border control to verify that they correspond to the same identity. To this purpose, in this study, we analyze the locations of biologically meaningful facial landmarks identified in the two images, with the goal of capturing inconsistencies in the facial geometry introduced by the morphing process. We report the results of extensive experiments performed on images of various sources and under different experimental settings showing that landmark locations detected through automated algorithms contain discriminative information for identifying pairs with morphed passport photos. Sensitivity of supervised classifiers to different compositions on the training and testing sets are also explored, together with the performance of different derived feature transformations.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:6

Enthalten in:

Journal of imaging - 6(2020), 11 vom: 29. Okt.

Sprache:

Englisch

Beteiligte Personen:

Autherith, Stephanie [VerfasserIn]
Pasquini, Cecilia [VerfasserIn]

Links:

Volltext

Themen:

Automatic border control
Face landmarks
Face morphing
Forensics detection
Journal Article

Anmerkungen:

Date Revised 03.09.2021

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/jimaging6110115

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM330033255