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Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging
by
Popowicz, Adam
, Farah, Alejandro
, Fiolka, Jerzy
, Bernacki, Krzysztof
in
Artificial Intelligence
/ Biometrics
/ Biometry
/ Cameras
/ Computer vision
/ Diagnostic Imaging
/ finger vasculature
/ Fingers - diagnostic imaging
/ Humans
/ image processing
/ Mathematical functions
/ Operating systems
/ Pattern recognition systems
/ Upper Extremity
2023
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Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging
by
Popowicz, Adam
, Farah, Alejandro
, Fiolka, Jerzy
, Bernacki, Krzysztof
in
Artificial Intelligence
/ Biometrics
/ Biometry
/ Cameras
/ Computer vision
/ Diagnostic Imaging
/ finger vasculature
/ Fingers - diagnostic imaging
/ Humans
/ image processing
/ Mathematical functions
/ Operating systems
/ Pattern recognition systems
/ Upper Extremity
2023
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Do you wish to request the book?
Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging
by
Popowicz, Adam
, Farah, Alejandro
, Fiolka, Jerzy
, Bernacki, Krzysztof
in
Artificial Intelligence
/ Biometrics
/ Biometry
/ Cameras
/ Computer vision
/ Diagnostic Imaging
/ finger vasculature
/ Fingers - diagnostic imaging
/ Humans
/ image processing
/ Mathematical functions
/ Operating systems
/ Pattern recognition systems
/ Upper Extremity
2023
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Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging
Journal Article
Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging
2023
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Overview
Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using modern artificial intelligence algorithms. However, the quality of the data and the way in which it is obtained determines equally the effectiveness of identification. In this article, we present a novel device for extracting vision data from the internal as well as external structures of the human finger. We use spatially selective backlight consisting of NIR diodes of three wavelengths. The fast image acquisition allows for insight into the pulse waveform. Thanks to the external illuminator, images of the skin folds of the finger are acquired as well. This rich collection of images is expected to significantly enhance identification capabilities using existing and future classic and AI-based computer vision techniques. Sample data from our device, before and after data processing, have been shared in a publicly available database.
Publisher
MDPI AG,MDPI
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