Multispectral Biometrics System Framework: Application to Presentation Attack Detection

In this work, we present a general framework for building a biometrics system capable of capturing multispectral data from a series of sensors synchronized with active illumination sources. The framework unifies the system design for different biometric modalities and its realization on face, finger...

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Bibliographic Details
Published in:IEEE sensors journal 2021-07, Vol.21 (13), p.15022-15041
Main Authors: Spinoulas, Leonidas, Hussein, Mohamed E., Geissbuhler, David, Mathai, Joe, Almeida, Oswin G., Clivaz, Guillaume, Marcel, Sebastien, Abdalmageed, Wael
Format: Article
Language:English
Subjects:
Biometrics
Biometrics system framework
Biosensors
Data acquisition
Data collection
Faces
Hardware
Lighting
multispectral biometrics
multispectral cameras
presentation attack detection
Sensors
Software
Synchronization
Systems design
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Summary:In this work, we present a general framework for building a biometrics system capable of capturing multispectral data from a series of sensors synchronized with active illumination sources. The framework unifies the system design for different biometric modalities and its realization on face, finger and iris data is described in detail. To the best of our knowledge, the presented design is the first to employ such a diverse set of electromagnetic spectrum bands, ranging from visible to long-wave-infrared wavelengths, and is capable of acquiring large volumes of data in seconds, which enabled us to successfully conduct a series of data collection events. We also present a comprehensive analysis on the captured data using a deep-learning classifier for presentation attack detection. Our analysis follows a data-centric approach attempting to highlight the strengths and weaknesses of each spectral band at distinguishing live from fake samples.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2021.3074406