DeepAI AI Chat
Log In Sign Up

Analyzing Human Observer Ability in Morphing Attack Detection – Where Do We Stand?

by   Sankini Rancha Godage, et al.

While several works have studied the vulnerability of automated FRS and have proposed morphing attack detection (MAD) methods, very few have focused on studying the human ability to detect morphing attacks. The examiner/observer's face morph detection ability is based on their observation, domain knowledge, experience, and familiarity with the problem, and no works report the detailed findings from observers who check identity documents as a part of their everyday professional life. This work creates a new benchmark database of realistic morphing attacks from 48 unique subjects leading to 400 morphed images presented to the observers in a Differential-MAD (D-MAD) setting. Unlike the existing databases, the newly created morphed image database has been created with careful considerations to age, gender and ethnicity to create realistic morph attacks. Further, unlike the previous works, we also capture ten images from Automated Border Control (ABC) gates to mimic the realistic D-MAD setting leading to 400 probe images in border crossing scenarios. The newly created dataset is further used to study the ability of human observers' ability to detect morphed images. In addition, a new dataset of 180 morphed images is also created using the FRGCv2 dataset under the Single Image-MAD (S-MAD) setting. Further, to benchmark the human ability in detecting morphs, a new evaluation platform is created to conduct S-MAD and D-MAD analysis. The benchmark study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmental employees from more than 40 countries. The analysis provides interesting insights and points to expert observers' missing competence and failure to detect a considerable amount of morphing attacks. Human observers tend to detect morphed images to a lower accuracy as compared to the automated MAD algorithms evaluated in this work.


page 3

page 11

page 12

page 14

page 15

page 34

page 35

page 36


Morphing Attack Detection – Database, Evaluation Platform and Benchmarking

Morphing attacks have posed a severe threat to Face Recognition System (...

Multispectral Imaging for Differential Face Morphing Attack Detection: A Preliminary Study

Face morphing attack detection is emerging as an increasingly challengin...

Deep Face Representations for Differential Morphing Attack Detection

The vulnerability of facial recognition systems to face morphing attacks...

On the Influence of Ageing on Face Morph Attacks: Vulnerability and Detection

Face morphing attacks have raised critical concerns as they demonstrate ...

Algorithmic Fairness in Face Morphing Attack Detection

Face morphing attacks can compromise Face Recognition System (FRS) by ex...

Robust Morph-Detection at Automated Border Control Gate using Deep Decomposed 3D Shape and Diffuse Reflectance

Face recognition is widely employed in Automated Border Control (ABC) ga...