Face Feature Visualisation of Single Morphing Attack Detection
- URL: http://arxiv.org/abs/2304.13021v1
- Date: Tue, 25 Apr 2023 17:51:23 GMT
- Title: Face Feature Visualisation of Single Morphing Attack Detection
- Authors: Juan Tapia and Christoph Busch
- Abstract summary: This paper proposes an explainable visualisation of different face feature extraction algorithms.
It enables the detection of bona fide and morphing images for single morphing attack detection.
The visualisation may help to develop a Graphical User Interface for border policies.
- Score: 13.680968065638108
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: 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.
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