Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real-world applications. The deployment of this technology raises questions about the main vulnerabilities and security threats related to these systems. Among these threats, presentation attacks stand out as some of the most relevant and studied. Presentation attacks can be defined as the presentation of human characteristics or artifacts directly to the capture device of a biometric system trying to interfere with its normal operation. In the case of the iris, these attacks include the use of real irises as well as artifacts with different levels of sophistication such as photographs or videos. This chapter introduces iris Presentation Attack Detection (PAD) methods that have been developed to reduce the risk posed by presentation attacks. First, we summarize the most popular types of attacks including the main challenges to address. Second, we present a taxonomy of PAD methods as a brief introduction to this very active research area. Finally, we discuss the integration of these methods into iris recognition systems according to the most important scenarios of practical application.
mehr| Titel | Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances |
|---|---|
| Medien | Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Singapore |
| Verlag | Springer, Singapore |
| Band | 2 |
| ISBN | 978-981-19-5287-6 |
| Verfasser | Aythami Morales, Julian Fierrez, Javier Galbally, Prof. Dr. Marta Gomez-Barrero |
| Seiten | 103-121 |
| Veröffentlichungsdatum | 24.02.2023 |
| Projekttitel | RESPECT |
| Zitation | Morales, Aythami; Fierrez, Julian; Galbally, Javier; Gomez-Barrero, Marta (2023): Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances. Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Singapore 2, 103-121. DOI: 10.1007/978-981-19-5288-3_5 |