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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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The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
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Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) Descriptor for Iris Liveness Detection.

Rohit Agarwal1, Anand Singh Jalal1, K V Arya2

  • 1Department of Computer Engineering and Applications, GLA University, Mathura, Uttar Pradesh 281406 India.

Wireless Personal Communications
|August 25, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces an Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) to detect fake irises, a common biometric security vulnerability. The new method improves accuracy in identifying genuine irises against presentation attacks.

Keywords:
Feature descriptorForged iris liveness detectionSpoof attack

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Area of Science:

  • Computer Science
  • Biometrics
  • Security Engineering

Background:

  • Biometric systems are widely used for automatic person recognition.
  • Iris biometrics offer high accuracy but are vulnerable to presentation attacks like spoofing.
  • Existing liveness detection methods struggle with sophisticated artificial iris artifacts.

Purpose of the Study:

  • To propose a novel feature descriptor for enhanced iris liveness detection.
  • To address the challenge of presentation attacks in iris recognition systems.
  • To improve the robustness of biometric security against forged iris detection.

Main Methods:

  • Development of the Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) descriptor.
  • Exploration of the relationship between central pixels and their hexagonal neighbors.
  • Testing the proposed approach on the ATVS-FIR DB and IIIT-D CLI databases.

Main Results:

  • The EBHXEP descriptor demonstrated superior performance in detecting forged irises.
  • The proposed method achieved improved accuracy in iris liveness detection.
  • A reduced average error rate was observed compared to existing methods.

Conclusions:

  • The EBHXEP is an effective feature descriptor for robust iris liveness detection.
  • This research contributes to enhancing the security of biometric systems against presentation attacks.
  • The findings suggest a significant advancement in combating iris spoofing techniques.