2018
DOI: 10.1049/iet-bmt.2017.0147
|View full text |Cite
|
Sign up to set email alerts
|

Extended StirTrace benchmarking of biometric and forensic qualities of morphed face images

Abstract: Since its introduction in 2014, the face morphing forgery (FMF) attack has received significant attention from the biometric and media forensic research communities. The attack aims at creating artificially weakened templates which can be successfully matched against multiple persons. If successful, the attack has an immense impact on many biometric authentication scenarios including the application of electronic machine-readable travel document (eMRTD) at automated border control gates. We extend the StirTrac… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
52
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
4
2
2

Relationship

1
7

Authors

Journals

citations
Cited by 72 publications
(54 citation statements)
references
References 26 publications
0
52
0
Order By: Relevance
“…The second validation set we use is the "AMSL Face Morph Image Data Set" dataset introduced in [23]. These morphs were created using images from [24] and [25].…”
Section: Validation Setsmentioning
confidence: 99%
“…The second validation set we use is the "AMSL Face Morph Image Data Set" dataset introduced in [23]. These morphs were created using images from [24] and [25].…”
Section: Validation Setsmentioning
confidence: 99%
“…For our paper, we use three state-of-the-art morph generation pipelines (MGP) to create three dierent types of face morphing for our evalatuion dats sets from two related works [19,24]. As mentioned in [30], all morph pipelines are based on alpha-blending and warping.…”
Section: Morph Generation Pipelinesmentioning
confidence: 99%
“…• The combined morph is the third MGP used and combines the aforementioned pipelines to avoid shortcomings. The pipeline is introduced in [24] and aligns the original images prior to the warping process to ensure that warping does not lead to a distortion of the face geometry. This MGP has the best visual quality of the three mentioned pipelines as well as a high biometric quality [24].…”
Section: Morph Generation Pipelinesmentioning
confidence: 99%
See 1 more Smart Citation
“…Reillo et al [15] have used attribute-based identification of varied signatures of humans by extracting the geometric attributes. The work of Neubert et al [16] has presented a solution towards resisting forging face shape based attack using a morphing based approach for better biometric security. Guo et al [17] have carried out an identification of the image based on forged color information using histogram-based as well as an attribute-based encoding mechanism.…”
Section: Introductionmentioning
confidence: 99%