Face verification is widely used for Automated Border Control (ABC) in many countries. But such ABC systems are vulnerable to Morphing Attacks (MAs), where a morphed face image is submitted to apply for a passport. To counter face MAs, this paper proposes to detect morphed face images and identify morphing attackers by the use of a watchlist. It is carried out by comparing a suspect image with the biometric references contained in a watchlist, and its detection process is accomplished by analyzing the results of face comparison. Once a morphed image is detected, its morphing attacker is also identified. Meanwhile, a database with different morphing methods, image qualities, facial expressions, and face angles is collected. Experimental results and analysis show that it can achieve stable detection and attacker identification performance for 4 different face MAs, and it can well generalize to unseen morphing types and weights. Moreover, it has good robustness to variations of image qualities, facial expressions, and face angles.

人脸验证在许多国家被广泛用于自动边境控制 (ABC)。但是这样的 ABC 系统很容易受到变形攻击 (MA) 的攻击，在这种攻击中，需要提交变形的面部图像以申请护照。为了对抗面部 MA，本文提出通过使用监视列表来检测变形的面部图像并识别变形的攻击者。它通过将可疑图像与监视列表中包含的生物特征参考进行比较来执行，其检测过程是通过分析面部比较的结果来完成的。一旦检测到变形图像，它的变形攻击者也会被识别。同时，收集了具有不同变形方法、图像质量、面部表情和面部角度的数据库。实验结果和分析表明，它可以对 4 种不同的人脸 MA 实现稳定的检测和攻击者识别性能，并且可以很好地推广到看不见的变形类型和权重。此外，它对图像质量、面部表情和面部角度的变化具有良好的鲁棒性。