Liveness iris detection method based on the eye's optical features

He, Yuqing; Hou, Yushi; Li, Ying-jiao; Wang, Yueming

doi:10.1117/12.868899

Cited by 10 publications

(1 citation statement)

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“…• Multispectral imaging [37,44,46,51]: The eye includes complex anatomical structures enclosed in three layers. These layers are made of organic tissue with different spectrographic properties.…”

Section: Hardware-based Approachesmentioning

confidence: 99%

Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances

Morales¹,

Fiérrez²,

Galbally³

et al. 2021

Preprint

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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 presentation of human characteristics or artifacts directly to the capture device of a biometric system trying to interfere its normal operation. In the case of the iris, these attacks include the use of real irises as well as artifacts with different level 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 summarise the most popular types of attacks including the main challenges to address. Secondly, we present a taxonomy of Presentation Attack Detection 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.

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Section: Hardware-based Approachesmentioning

confidence: 99%