Dataset Information

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

ABSTRACT: 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.

SUBMITTER: Fiolka J

PROVIDER: S-EPMC9962154 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

Fiolka Jerzy J Bernacki Krzysztof K Farah Alejandro A Popowicz Adam A

Sensors (Basel, Switzerland) 20230210 4

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 inter ...[more]

PMID: 36850577

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Project description:Aggregation induced emission (AIE)-active bright two-photon fluorescent probes with second near-infrared (NIR-II) light excitability can be used for efficient brain bioimaging studies, wherein the fabrication of water-dispersible nanoparticles by encapsulating the hydrophobic probes with amphiphilic polymer holds the key to ensuring biocompatibility and in vivo adaptability. However, barely any study has evaluated the structural requirements that can substantially affect the water-dispersible nanoparticle formation ability of an organic AIE-active dye with amphiphilic polymers. The present study systematically assessed the structural dependency of a well-known acrylonitrile based AIE system/fluorogenic core upon the formation of water-dispersible nanoparticles and elucidated how the structural modifications can impact the in vivo two-photon imaging. Methods: A total of four acrylonitrile-based aggregation induced emission (AIE)-active two-photon (TP) fluorescent probes (AIETP, AIETP C1, AIETP C2 and AIETP C3) have been judiciously designed and synthesized with structural variations to realize how the structural alterations could substantially influence the water-dispersible nanoparticle formation ability (with amphiphilic polymers) and photo-stability to impact the in vivo imaging. Results: It has been found that the incorporation of the phenyl-thiazole unit in AIETP, AIETP C2 and AIETP C3 facilitated the formation of water-dispersible nanoparticles (NPs) with amphiphilic polymers (Pluronic F127) whereas the presence of only phenyl moiety instead in AIETP C1 could not meet the suitable condition to form the NPs with good aqueous dispersibility. Rationally designed AIETP NPs that exhibited higher brightness, improved photostability and good two-photon absorption cross section was successfully employed for in vivo brain vasculature imaging. Conclusions: Robust noninvasive 2D and 3D two-photon (NIR-II light, 1040 nm) brain vasculature imaging with beneficial attributes such as outstanding penetration depth (800 µm) and exceptional spatial resolution (1.92 µm), were achieved by utilizing AIETP NPs in this study.

Dataset Information

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

Publications

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.

Similar Datasets

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