Title
Simulation of Print-Scan Transformations for Face Images based on Conditional Adversarial Networks.
Abstract
In many countries, printing and scanning of face images is frequently performed as part of the issuance process of electronic travel documents, e.g., ePassports. Image alterations induced by such print-scan transformations may negatively effect the performance of various biometric sub-systems, in particular image manipulation detection. Consequently, according training data is needed in order to achieve robustness towards said transformations. However, manual printing and scanning is time-consuming and costly.In this work, we propose a simulation of print-scan transformations for face images based on a Conditional Generative Adversarial Network (cGAN). To this end, subsets of two public face databases are manually printed and scanned using different printer-scanner combinations. A cGAN is then trained to perform an image-to-image translation which simulates the corresponding print-scan transformations. The goodness of simulation is evaluated with respect to image quality, biometric sample quality and performance, as well as human assessment.
Year
Venue
Keywords
2020
2020 International Conference of the Biometrics Special Interest Group (BIOSIG)
Biometrics,face,print-scan transformation,simulation,generative adversarial network
DocType
ISBN
Citations 
Conference
978-3-88579-700-5
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Aleksandar Mitkovski100.34
Johannes Merkle27512.14
Christian Rathgeb355155.72
Benjamin Tams4534.90
Kevin Bernardo500.34
Nathania E. Haryanto600.34
Christoph Busch726850.22