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Compressed sensing approach for wrist vein biometrics
Author(s) -
Lantsov Aleksey,
Ryabko Maxim,
Shchekin Aleksey
Publication year - 2018
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201700153
Subject(s) - wearable computer , biometrics , computer science , compressed sensing , artificial intelligence , wrist , computer vision , pixel , wearable technology , photodiode , authentication (law) , computer hardware , embedded system , computer security , medicine , materials science , optoelectronics , radiology
The work describes features of the compressed sensing (CS) approach utilized for development of a wearable system for wrist vein recognition with single‐pixel detection; we consider this system useful for biometrics authentication purposes. The CS approach implies use of a spatial light modulation (SLM) which, in our case, can be performed differently—with a liquid crystal display or diffusely scattering medium. We show that compressed sensing combined with above‐mentioned means of SLM allows us to avoid using an optical system—a limiting factor for wearable devices. The trade‐off between the 2 different SLM approaches regarding issues of practical implementation of CS approach for wrist vein recognition purposes is discussed. A possible solution of a misalignment problem—a typical issue for imaging systems based upon 2D arrays of photodiodes—is also proposed. Proposed design of the wearable device for wrist vein recognition is based upon single‐pixel detection.