Detecting morphed face images using facial landmarks

Ulrich Scherhag, Dhanesh Budhrani, Marta Gomez-Barrero, Christoph Busch

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Abstract

With the widespread deployment of automatic biometric recognition systems, some security issues have been unveiled. In particular, face recognition systems have been recently shown to be vulnerable to attacks carried out with morphed face images. Such synthetic images can be defined as the fusion of the face images of two (or more) different subjects. The associated risk lies on the ability of multiple subjects to be positively verified with a single enrolled morphed face image. As common texture based features have limited capabilities to tackle this problem, we propose a novel method for morphed face image detection, based on the computation of the differences between the landmarks of a probe bona fide (i.e., captured under supervision) image of the attacker, and the landmarks of the enrolled image (i.e., the suspected morphed image). In this work, a new database is created for the experiments, comprising both bona fide and morphed images created with two different morphing methods. The experiments show that for the detection task, the proposed algorithm achieves Equal Error Rates at 32.7%.
Original languageEnglish
Title of host publicationImage and Signal Processing : 8th International Conference, ICISP 2018, Cherbourg, France, July 2-4, 2018, Proceedings
EditorsAlamin Mansouri , Abderrahim El Moataz , Fathallah Nouboud , Driss Mammass
Number of pages9
Volume10884
PublisherSpringer
Publication date2018
Pages444-452
ISBN (Print)978-3-319-94210-0
ISBN (Electronic)978-3-319-94211-7
DOIs
Publication statusPublished - 2018
Event8th International Conference on Image and Signal Processing - Cherbourg, France
Duration: 2 Jul 20184 Jul 2018

Conference

Conference8th International Conference on Image and Signal Processing
CountryFrance
CityCherbourg
Period02/07/201804/07/2018
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN0302-9743

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