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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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 C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
IR Spectrum01:19

IR Spectrum

When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0% (complete...
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

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 stretching vibration...
UV–Vis Spectroscopy of Conjugated Systems01:32

UV–Vis Spectroscopy of Conjugated Systems

Organic compounds with conjugated double bonds show strong absorption features in the UV–visible region of the electromagnetic spectrum attributed to π → π* electronic excitations. Generally, a UV–vis absorption spectrum is recorded as a plot of absorbance vs wavelength. The wavelength of maximum absorbance, which manifests as a peak in the absorption spectrum, is denoted as λmax.
One of the factors influencing λmax is the extent of conjugation in the...
IR Absorption Frequency: Hybridization01:21

IR Absorption Frequency: Hybridization

Hydrocarbons such as alkanes, alkenes, and alkynes show characteristic C–H stretching absorption bands. These IR stretching frequencies depend on the hybridization of the involved carbon atom and can be explained in terms of the s character of each hybridized atomic orbital.
Among the sp, sp2, and sp3 hybridized orbitals, sp orbitals have the maximum s character (50%). Consequently, the electrons are held more closely to the nucleus, resulting in stronger and shorter C–H bonds that stretch at a...

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RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
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Optimal wavelength band clustering for multispectral iris recognition.

Yazhuo Gong1, David Zhang, Pengfei Shi

  • 1Institute of Image Processing & Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China.

Applied Optics
|July 10, 2012
PubMed
Summary

This study identifies optimal spectral bands for iris recognition. Clustering wavelengths revealed three key bands enhance multispectral iris fusion and recognition performance.

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Area of Science:

  • Biometrics
  • Computer Vision
  • Optical Engineering

Background:

  • Iris recognition systems utilize unique iris textures for identification.
  • Multispectral imaging captures detailed iris patterns across various wavelengths.
  • Optimizing spectral bands is crucial for enhancing multispectral iris fusion and recognition accuracy.

Purpose of the Study:

  • To determine the optimal number and selection of spectral bands for effective iris multispectral fusion.
  • To enhance the performance of iris multispectral recognition systems.
  • To investigate wavelength clustering based on iris texture dissimilarity.

Main Methods:

  • Designed a multispectral acquisition system for iris imaging (420-940 nm).
  • Acquired 60 human iris images from 30 subjects.
  • Applied agglomerative clustering based on 2D Principal Component Analysis (PCA) to 10 feature bands.

Main Results:

  • Identified three clusters of spectral wavelengths as sufficient for representing iris texture features.
  • Determined the optimal number, center, and composition of these spectral wavelength clusters.
  • Demonstrated higher performance in iris multispectral recognition using a three-wavelength-band fusion approach.

Conclusions:

  • Three spectral wavelength clusters effectively represent iris texture features for multispectral analysis.
  • Fusion of three selected spectral bands significantly improves iris multispectral recognition performance.
  • This wavelength selection method provides a foundation for optimizing multispectral iris recognition systems.