Supporting Human Examiners in Facial Image Manipulation Detection

Many countries lack live enrollment procedures for facial images in identity documents, allowing citizens to provide their own photos. This operational procedure opens avenues for fraudulent attacks, primarily through digital manipulations of facial images, which have an impact on automated identity verification performance. Detecting such manipulations before image inclusion into documents is critical, especially given the difficulty in identifying them visually. To address this, a software tool is proposed to assist human examiners in analyzing facial images for electronic ID documents. The tool aligns with guide-lines from the Facial Identification Scientific Working Group, implementing measures covering various facial components to ease the comparison between the ID photo and a live-captured image during enrollment.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/metroxraine62247.2024.10797036
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Supporting Human Examiners in Facial Image Manipulation Detection

Davide Maltoni, Annalisa Franco, Maichol Dadi
Face recognition and analysis
article

Supporting Human Examiners in Facial Image Manipulation Detection

Davide Maltoni, Annalisa Franco, Maichol Dadi
article en

Abstract

Many countries lack live enrollment procedures for facial images in identity documents, allowing citizens to provide their own photos. This operational procedure opens avenues for fraudulent attacks, primarily through digital manipulations of facial images, which have an impact on automated identity verification performance. Detecting such manipulations before image inclusion into documents is critical, especially given the difficulty in identifying them visually. To address this, a software tool is proposed to assist human examiners in analyzing facial images for electronic ID documents. The tool aligns with guide-lines from the Facial Identification Scientific Working Group, implementing measures covering various facial components to ease the comparison between the ID photo and a live-captured image during enrollment.

University of Bologna (IT)
Gender equality
Openalex Percentile: Top 76%
Face recognition and analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.