Research on Face Image Morphing Based on Automatic Feature Detection

Tian, Guanglai; Chen, Chi-Cheng; Sun, Gengxin; Bin, Sheng

doi:10.1109/ecbios50299.2020.9203749

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…In terms of required interaction, approaches range from manual [26], [27] or semi-automated [28] to 1 Germany bans digital doppelgänger passport photos, Reuters (2020) [21].…”

Section: A Digital Face Image Manipulationsmentioning

confidence: 99%

Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations

et al. 2022

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In recent years, increasing deployment of face recognition technology in security-critical settings, such as border control or law enforcement, has led to considerable interest in the vulnerability of face recognition systems to attacks utilising legitimate documents, which are issued on the basis of digitally manipulated face images. As automated manipulation and attack detection remains a challenging task, conventional processes with human inspectors performing identity verification remain indispensable. These circumstances merit a closer investigation of human capabilities in detecting manipulated face images, as previous work in this field is sparse and often concentrated only on specific scenarios and biometric characteristics. This work introduces a web-based, remote visual discrimination experiment on the basis of principles adopted from the field of psychophysics and subsequently discusses interdisciplinary opportunities with the aim of examining human proficiency in detecting different types of digitally manipulated face images, specifically face swapping, morphing, and retouching. In addition to analysing appropriate performance measures, a possible metric of detectability is explored. Experimental data of 306 probands indicate that detection performance is widely distributed across the population and detection of certain types of face image manipulations is much more challenging than others.

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“…In terms of required interaction, approaches range from manual [26], [27] or semi-automated [28] to 1 Germany bans digital doppelgänger passport photos, Reuters (2020) [21].…”

Section: A Digital Face Image Manipulationsmentioning

confidence: 99%

Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations

et al. 2022

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“…Then, a warping process is conducted to generate the morphed image [32], [33]. In this section, we will introduce the general face morphing methodology based on automatic facial feature point detection and triangulation warping [34].…”

Section: B Image Morphingmentioning

confidence: 99%

Steganographic Secret Sharing With GAN-Based Face Synthesis and Morphing for Trustworthy Authentication in IoT

2021

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Trust and security are fundamental to the successful adoption of the Internet of Things (IoT). This paper proposes a secure message authentication scheme based on steganographic secret sharing for building trust in IoT systems. In our scheme, the message is split and distributed to two participants by a dealer, and it can be revealed only when the two authorized participants grant their consents. Neither of the participants can disclose the message without the consent of the other. To avoid malicious cyberattacks in IoT communications, each share of message is concealed in the form of a human face image, referred to as the shadow image, via a generative adversarial network (GAN). For each participant, a convolutional neural network (CNN) is trained to extract the share of message from the shadow image generated with the participant's key. Distortions and alterations to the shadow images may occur during the transmission from the dealer to the participant. As a tamper-evident design, each shadow image is morphed with the participant's source image under the participant's customized morphing parameter. Cheater detection is also crucial for involved participants to identify fake shadow images during the secret retrieval process. As a cheating countermeasure, the shadow image for one participant is morphed with that for the other and then morphed further with the given source image. The proposed scheme enables multi-factor authentication in the sense that the message is protected by the keys, source images, and morphing parameters of two participants.

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Reproducing Asymmetries Caused by Breast Cancer Treatment in Pre-Operative Breast Images

Freitas,

Montenegro,

Cardoso

et al. 2024

2024 IEEE International Symposium on Biomedical Imaging (ISBI)

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Research on Face Image Morphing Based on Automatic Feature Detection

Cited by 3 publications

References 6 publications

Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations

Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations

Steganographic Secret Sharing With GAN-Based Face Synthesis and Morphing for Trustworthy Authentication in IoT

Reproducing Asymmetries Caused by Breast Cancer Treatment in Pre-Operative Breast Images

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