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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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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 sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
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Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
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Fingerprint matching using the onion peeling approach and turning function.

Nazanin Padkan1, B Sadeghi Bigham2, Mohammad Reza Faraji1

  • 1Department of Computer Science and Information Technology, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran.

Gene Expression Patterns : GEP
|December 13, 2022
PubMed
Summary

This study introduces a novel minutiae-based fingerprint matching algorithm using the onion peeling approach. The method aligns fingerprints, constructs convex polygons from matched minutiae, and compares them using turning function distance for improved accuracy.

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Area of Science:

  • Biometrics
  • Computer Science
  • Computational Geometry

Background:

  • Fingerprint matching is crucial for automatic identification systems.
  • Minutiae-based algorithms, focusing on ridge endings and bifurcations, are widely used.
  • Existing methods face challenges in accuracy and efficiency.

Purpose of the Study:

  • To present a new minutiae-based fingerprint matching algorithm.
  • To utilize the onion peeling approach for enhanced fingerprint comparison.
  • To evaluate the algorithm's performance and effectiveness.

Main Methods:

  • Fingerprint alignment to identify matched minutiae points.
  • Construction of nested convex polygons from matched minutiae.
  • Comparison of polygons using turning function distance.

Main Results:

  • The onion peeling approach demonstrates simplicity, accuracy, and low time complexity.
  • Evaluation on the FVC2002 database shows promising results.
  • Filtering based on layer difference and minutiae score improves performance.

Conclusions:

  • The proposed onion peeling method offers an effective solution for fingerprint matching.
  • The algorithm's computational geometry basis contributes to its efficiency.
  • This approach enhances accuracy and reduces complexity in biometric identification.