Jove
Visualize
Contact Us

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comparison of Training Strategies for Autoencoder-Based Monochromatic Image Denoising.

Sensors (Basel, Switzerland)·2023
Same author

SUTO-Solar Through-Turbulence Open Image Dataset.

Sensors (Basel, Switzerland)·2022
Same author

A Contemporary Design Process for Single-Phase Voltage Source Inverter Control Systems.

Sensors (Basel, Switzerland)·2022
Same author

Smart SDN Management of Fog Services to Optimize QoS and Energy.

Sensors (Basel, Switzerland)·2021
Same author

Modified Distance Transformation for ImageEnhancement in NIR Imaging of Finger Vein System.

Sensors (Basel, Switzerland)·2020
Same author

Unmet goals in the treatment of Acute Myocardial Infarction: Review.

F1000Research·2017
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Aug 8, 2025

Dual-mode Imaging of Cutaneous Tissue Oxygenation and Vascular Function
11:35

Dual-mode Imaging of Cutaneous Tissue Oxygenation and Vascular Function

Published on: December 8, 2010

16.6K

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

Jerzy Fiolka1, Krzysztof Bernacki1, Alejandro Farah2

  • 1Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

Sensors (Basel, Switzerland)
|February 28, 2023
PubMed
Summary

A new device captures internal and external finger data for enhanced biometrics. This novel approach, using multi-wavelength near-infrared light, improves personal identification accuracy with advanced computer vision and AI techniques.

Keywords:
biometryfinger vasculatureimage processing

More Related Videos

Universal Hand-held Three-dimensional Optoacoustic Imaging Probe for Deep Tissue Human Angiography and Functional Preclinical Studies in Real Time
09:56

Universal Hand-held Three-dimensional Optoacoustic Imaging Probe for Deep Tissue Human Angiography and Functional Preclinical Studies in Real Time

Published on: November 4, 2014

10.8K
Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research
06:40

Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research

Published on: June 8, 2022

1.9K

Related Experiment Videos

Last Updated: Aug 8, 2025

Dual-mode Imaging of Cutaneous Tissue Oxygenation and Vascular Function
11:35

Dual-mode Imaging of Cutaneous Tissue Oxygenation and Vascular Function

Published on: December 8, 2010

16.6K
Universal Hand-held Three-dimensional Optoacoustic Imaging Probe for Deep Tissue Human Angiography and Functional Preclinical Studies in Real Time
09:56

Universal Hand-held Three-dimensional Optoacoustic Imaging Probe for Deep Tissue Human Angiography and Functional Preclinical Studies in Real Time

Published on: November 4, 2014

10.8K
Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research
06:40

Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research

Published on: June 8, 2022

1.9K

Area of Science:

  • Biometrics and Human-Computer Interaction
  • Computer Vision and Image Analysis
  • Artificial Intelligence in Security

Background:

  • Personal identification relies heavily on human finger characteristics, driving research into advanced feature extraction and analysis.
  • Effectiveness of biometric identification is significantly influenced by data quality and acquisition methods.
  • Current methods often focus on external features, with limited exploration of internal finger structures.

Purpose of the Study:

  • To introduce a novel device for comprehensive vision data extraction from both internal and external human finger structures.
  • To leverage multi-wavelength near-infrared (NIR) illumination for enhanced data acquisition.
  • To improve personal identification capabilities through richer, multi-modal finger data.

Main Methods:

  • Development of a device utilizing spatially selective backlight with NIR diodes of three wavelengths.
  • Implementation of fast image acquisition to capture pulse waveforms from internal structures.
  • Integration of an external illuminator for acquiring images of external skin folds.

Main Results:

  • The device successfully captures detailed internal and external finger data, including pulse waveforms and skin fold images.
  • Acquired data provides a rich dataset expected to significantly enhance identification capabilities.
  • Sample data, pre- and post-processing, has been made publicly available.

Conclusions:

  • The novel device offers a significant advancement in biometric data acquisition for human finger identification.
  • Combining internal and external finger data acquisition provides a more robust foundation for AI-based and traditional computer vision techniques.
  • The publicly shared dataset facilitates further research and development in the field of biometrics.