This paper proposes an explainable visualisation of different face feature
extraction algorithms that enable the detection of bona fide and morphing
images for single morphing attack detection. The feature extraction is based on
raw image, shape, texture, frequency and compression. This visualisation may
help to develop a Graphical User Interface for border policies and specifically
for border guard personnel that have to investigate details of suspect images.
A Random forest classifier was trained in a leave-one-out protocol on three
landmarks-based face morphing methods and a StyleGAN-based morphing method for
which morphed images are available in the FRLL database. For morphing attack
detection, the Discrete Cosine-Transformation-based method obtained the best
results for synthetic images and BSIF for landmark-based image features.

本文提出了一种可解释的面部特征提取算法，能够检测真实和变形图像，用于单一变形攻击检测。该方法基于原始图像、形状、纹理、频率和压缩。利用此方法可以开发一个图形用户界面来协助边境警卫人员调查涉嫌的图像。在三种基于地标点的人脸变形方法和基于 StyleGAN 的变形方法上进行随机森林分类器的训练，其中 FRLL 数据库提供了变形图像。用于变形攻击检测，离散余弦变换方法在合成图像上获得了最佳结果，基于地标点的图像特征使用 BSIF 进行检测。