Fused Classification For Differential Face Morphing Detection

• URL: http://arxiv.org/abs/2309.00665v1
• Date: Fri, 1 Sep 2023 16:14:29 GMT
• Title: Fused Classification For Differential Face Morphing Detection
• Authors: Iurii Medvedev, Joana Pimenta, Nuno Gon\c{c}alves
• Abstract summary: Face morphing, a presentation attack technique, poses significant security risks to face recognition systems. Traditional methods struggle to detect morphing attacks, which involve blending multiple face images. We propose an extended approach based on fused classification method for no-reference scenario.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Face morphing, a sophisticated presentation attack technique, poses significant security risks to face recognition systems. Traditional methods struggle to detect morphing attacks, which involve blending multiple face images to create a synthetic image that can match different individuals. In this paper, we focus on the differential detection of face morphing and propose an extended approach based on fused classification method for no-reference scenario. We introduce a public face morphing detection benchmark for the differential scenario and utilize a specific data mining technique to enhance the performance of our approach. Experimental results demonstrate the effectiveness of our method in detecting morphing attacks.

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