Fang, Meiling ; Damer, Naser ; Boutros, Fadi ; Kirchbuchner, Florian ; Kuijper, Arjan (2021)
Cross-database and cross-attack Iris presentation attack detection using micro stripes analyses.
In: Image and Vision Computing, 105
doi: 10.1016/j.imavis.2020.104057
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
With the widespread use of mobile devices, iris recognition systems encounter more challenges, such as the vulnerability of Presentation Attack Detection (PAD). Recent works pointed out the contact lens attacks, especially images captured under the uncontrolled environment, as a hard task for iris PAD. In this paper, we propose a novel framework for detecting iris presentation attacks that especially for detecting contact lenses based on the normalized multiple micro stripes. The classification decision is made by the majority vote of those micro-stripes. An in-depth experimental evaluation of this framework reveals a superior performance in three databases compared with state-of-the-art (SoTA) algorithms and baselines. Moreover, our solution minimizes the confusion between textured (attack) and transparent (bona fide) presentations in comparison to SoTA methods. We support the rationalization of our proposed method by studying the significance of different pupil-centered eye areas in iris PAD decisions under different experimental settings. In addition, extensive cross-database and cross-attack (unknown attack) detection evaluation experiments are demonstrated to explore the generalizability of our proposed method, texture-based method, and neural network based methods in three different databases. The results indicate that our Micro Stripes Analyses (MSA) method has, in most experiments, better generalizability compared to other baselines.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Fang, Meiling ; Damer, Naser ; Boutros, Fadi ; Kirchbuchner, Florian ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Cross-database and cross-attack Iris presentation attack detection using micro stripes analyses |
| Sprache: | Englisch |
| Publikationsjahr: | Januar 2021 |
| Verlag: | Elsevier B.V. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Image and Vision Computing |
| Jahrgang/Volume einer Zeitschrift: | 105 |
| DOI: | 10.1016/j.imavis.2020.104057 |
| Kurzbeschreibung (Abstract): | With the widespread use of mobile devices, iris recognition systems encounter more challenges, such as the vulnerability of Presentation Attack Detection (PAD). Recent works pointed out the contact lens attacks, especially images captured under the uncontrolled environment, as a hard task for iris PAD. In this paper, we propose a novel framework for detecting iris presentation attacks that especially for detecting contact lenses based on the normalized multiple micro stripes. The classification decision is made by the majority vote of those micro-stripes. An in-depth experimental evaluation of this framework reveals a superior performance in three databases compared with state-of-the-art (SoTA) algorithms and baselines. Moreover, our solution minimizes the confusion between textured (attack) and transparent (bona fide) presentations in comparison to SoTA methods. We support the rationalization of our proposed method by studying the significance of different pupil-centered eye areas in iris PAD decisions under different experimental settings. In addition, extensive cross-database and cross-attack (unknown attack) detection evaluation experiments are demonstrated to explore the generalizability of our proposed method, texture-based method, and neural network based methods in three different databases. The results indicate that our Micro Stripes Analyses (MSA) method has, in most experiments, better generalizability compared to other baselines. |
| Freie Schlagworte: | Biometrics, Deep learning, Spoofing attacks, Iris recognition, Machine learning |
| Zusätzliche Informationen: | Art.No.: 104057 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 25 Mai 2021 08:02 |
| Letzte Änderung: | 25 Mai 2021 08:02 |
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