Title | ||
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Simulation of Print-Scan Transformations for Face Images based on Conditional Adversarial Networks. |
Abstract | ||
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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 |
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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 Mitkovski | 1 | 0 | 0.34 |
Johannes Merkle | 2 | 75 | 12.14 |
Christian Rathgeb | 3 | 551 | 55.72 |
Benjamin Tams | 4 | 53 | 4.90 |
Kevin Bernardo | 5 | 0 | 0.34 |
Nathania E. Haryanto | 6 | 0 | 0.34 |
Christoph Busch | 7 | 268 | 50.22 |