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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

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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 C=O, C=N, and C=C occur between 1600–1850 cm−1.
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Optimization based fingerprint direction field estimation.

Dongdong Nie1, Lizhuang Ma, XueZhong Xiao

  • 1Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ. China

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|February 7, 2007
PubMed
Summary

This study introduces a novel algorithm for fingerprint direction field estimation, improving accuracy by using global ridge characters to optimize squared gradients and reduce noise sensitivity.

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Area of Science:

  • Biometrics
  • Computer Vision
  • Signal Processing

Background:

  • Fingerprint direction field estimation is crucial for enhancement systems.
  • Current methods relying on local gradients are sensitive to noise, leading to inaccurate estimations in noisy regions.

Purpose of the Study:

  • To introduce an effective algorithm for accurate fingerprint direction field estimation.
  • To overcome the limitations of traditional gradient-based methods in noisy environments.

Main Methods:

  • Developed an algorithm utilizing global ridge characters.
  • Optimized the fingerprint direction field from squared gradients.

Main Results:

  • The proposed algorithm significantly improves the accuracy of ridge direction estimation.
  • Demonstrated effective noise reduction compared to traditional methods.

Conclusions:

  • The novel algorithm provides a more robust and accurate method for fingerprint direction field estimation.
  • This approach enhances fingerprint enhancement system performance by mitigating noise interference.