Impact of Image Context for Single Deep Learning Face Morphing Attack Detection

• URL: http://arxiv.org/abs/2309.00549v1
• Date: Fri, 1 Sep 2023 15:57:24 GMT
• Title: Impact of Image Context for Single Deep Learning Face Morphing Attack Detection
• Authors: Joana Pimenta, Iurii Medvedev, Nuno Gon\c{c}alves
• Abstract summary: Face recognition systems (FRSs) have become prevalent, but they are still vulnerable to image manipulation techniques such as face morphing attacks. This study investigates the impact of the alignment settings of input images on deep learning face morphing detection performance.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The increase in security concerns due to technological advancements has led to the popularity of biometric approaches that utilize physiological or behavioral characteristics for enhanced recognition. Face recognition systems (FRSs) have become prevalent, but they are still vulnerable to image manipulation techniques such as face morphing attacks. This study investigates the impact of the alignment settings of input images on deep learning face morphing detection performance. We analyze the interconnections between the face contour and image context and suggest optimal alignment conditions for face morphing detection.

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