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 s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
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| Series: | Journal of Imaging |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-433X/6/11/115 |
| _version_ | 1811153766743801856 |
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| author | Stephanie Autherith Cecilia Pasquini |
| author_facet | Stephanie Autherith Cecilia Pasquini |
| author_sort | Stephanie Autherith |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T15:14:53Z |
| format | Article |
| id | doaj.art-751b5c350a2e47818f6c923edc9c378c |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-10T15:14:53Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-751b5c350a2e47818f6c923edc9c378c2023-11-20T18:59:24ZengMDPI AGJournal of Imaging2313-433X2020-10-0161111510.3390/jimaging6110115Detecting Morphing Attacks through Face Geometry FeaturesStephanie Autherith0Cecilia Pasquini1Department of Computer Science, University of Innsbruck , Technikerstraße 21A, 6020 Innsbruck, AustriaDepartment of Information Engineering and Computer Science, University of Trento, Via Sommarive 9, 38123 Trento, ItalyFace-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.https://www.mdpi.com/2313-433X/6/11/115face morphingforensics detectionface landmarksautomatic border control |
| spellingShingle | Stephanie Autherith Cecilia Pasquini Detecting Morphing Attacks through Face Geometry Features Journal of Imaging face morphing forensics detection face landmarks automatic border control |
| title | Detecting Morphing Attacks through Face Geometry Features |
| title_full | Detecting Morphing Attacks through Face Geometry Features |
| title_fullStr | Detecting Morphing Attacks through Face Geometry Features |
| title_full_unstemmed | Detecting Morphing Attacks through Face Geometry Features |
| title_short | Detecting Morphing Attacks through Face Geometry Features |
| title_sort | detecting morphing attacks through face geometry features |
| topic | face morphing forensics detection face landmarks automatic border control |
| url | https://www.mdpi.com/2313-433X/6/11/115 |
| work_keys_str_mv | AT stephanieautherith detectingmorphingattacksthroughfacegeometryfeatures AT ceciliapasquini detectingmorphingattacksthroughfacegeometryfeatures |