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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

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Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
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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.
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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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IR Spectrum01:19

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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.
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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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A Study on Presentation Attack Detection in Thermal Infrared.

Marcin Kowalski1

  • 1Institute of Optoelectronics, Military University of Technology, 2 Gen. S. Kaliskiego St., 00-908 Warsaw, Poland.

Sensors (Basel, Switzerland)
|July 26, 2020
PubMed
Summary

Thermal infrared imaging enhances face recognition by detecting sophisticated presentation attacks. This study introduces a new dataset and a deep learning method to improve spoof detection accuracy.

Keywords:
facial counter spoofingpresentation attack detectionthermal face spoofing detectionthermal infrared

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Area of Science:

  • Biometrics
  • Computer Vision
  • Infrared Imaging

Background:

  • Traditional face recognition systems struggle with advanced presentation attacks.
  • Sophisticated spoofing methods are increasingly difficult to detect.
  • Thermal infrared imaging offers unique properties for enhanced detection.

Purpose of the Study:

  • Investigate the detection of face presentation attacks using thermal infrared imaging.
  • Analyze various spoofing methods including masks and photographs under different conditions.
  • Evaluate the impact of thermalization and subject state on detection accuracy.

Main Methods:

  • Analysis of thermal energy distribution on facial landmarks.
  • Investigation of printed/displayed photographs, 3D-printed, 3D-latex, and silicone masks.
  • Development and validation of a two-step deep learning-based detection method.
  • Introduction of a novel thermal face spoofing dataset.

Main Results:

  • Demonstrated the effectiveness of thermal imaging in distinguishing real faces from various spoofing attempts.
  • Quantified thermalization impact and subject state variations on spoof detection.
  • Validated deep learning models on diverse presentation attack instruments using the new dataset.

Conclusions:

  • Thermal infrared imaging significantly improves the robustness of face recognition against presentation attacks.
  • The proposed deep learning approach and dataset offer a promising direction for advanced spoof detection.
  • Further research can leverage thermal data for more secure biometric systems.