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Related Concept Videos

Veins of Upper Limbs01:17

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The human circulatory system, a marvel of biological engineering, is a complex network of vessels that transport blood throughout the body. Among these, the veins responsible for carrying blood from the upper limbs are divided into two categories: deep and superficial.
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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Related Experiment Video

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Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
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Robust finger vein ROI localization based on flexible segmentation.

Yu Lu1, Shan Juan Xie, Sook Yoon

  • 1Division of Electronic and Information Engineering, Chonbuk National University, Jeonju 561-756, Korea. dspark@jbnu.ac.kr.

Sensors (Basel, Switzerland)
|November 29, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a robust finger vein region of interest (ROI) localization method. The technique ensures high accuracy and real-time performance for finger vein identification systems, overcoming common image acquisition challenges.

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Area of Science:

  • Biometrics
  • Computer Vision
  • Image Processing

Background:

  • Finger vein patterns are effective for personal identification.
  • Image variations (translation, orientation, illumination) degrade biometric system performance by affecting region of interest (ROI) accuracy.

Purpose of the Study:

  • To develop a robust finger vein ROI localization method.
  • To enhance the accuracy and reliability of finger vein identification systems.

Main Methods:

  • A multi-step approach involving segmentation, orientation correction, and ROI detection.
  • Iterative refinement where segmentation and orientation calculations support each other for precise ROI localization.

Main Results:

  • Achieved 100% segmentation accuracy in experiments.
  • Demonstrated high robustness against various image acquisition challenges.
  • Average processing time of 22 ms per image, suitable for real-time applications.

Conclusions:

  • The proposed method significantly improves finger vein ROI localization accuracy and robustness.
  • The technique is suitable for real-time biometric identification systems.
  • Addresses key limitations in current finger vein recognition technologies.