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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...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
The Phase Rule01:20

The Phase Rule

The phase rule describes the relationship between the variance (degrees of freedom), the number of components, and the number of phases in a system at equilibrium.Variance is a concept that denotes the number of independent intensive properties (properties are those that do not depend on the amount of material in the system), such as temperature, pressure, and composition, that can be altered without impacting the number of phases in equilibrium.In a single-component system, such as pure water,...

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Updated: Jun 22, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Published on: March 18, 2019

Experimental evaluation of fingerprint verification system based on double random phase encoding.

Hiroyuki Suzuki, Masahiro Yamaguchi, Masuyoshi Yachida

    Optics Express
    |June 9, 2009
    PubMed
    Summary

    This study enhances smart card holder authentication by improving fingerprint verification accuracy. An optimized core detection method reduces the false rejection rate, ensuring more reliable security.

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    Area of Science:

    • Biometrics and Security Engineering
    • Computer Science and Information Technology

    Background:

    • Existing smart card authentication systems combining fingerprint and PIN verification face reduced accuracy with significant fingerprint shifts.
    • The double random phase encoding scheme, while innovative, presents challenges in maintaining verification accuracy under positional discrepancies.

    Purpose of the Study:

    • To review and enhance a smart card holder authentication system.
    • To propose a preprocessing method for improving the false rejection rate in fingerprint verification.
    • To address the issue of reduced accuracy due to fingerprint image shifts.

    Main Methods:

    • A review of a proposed smart card holder authentication system utilizing a double random phase encoding scheme.
    • Implementation of an optimized template for core detection to estimate positional differences between fingerprint images.
    • Introduction of a re-input mechanism for fingerprint verification when positional differences exceed a permissible threshold.

    Main Results:

    • The proposed preprocessing method effectively improves the false rejection rate (FRR).
    • Computational experiments confirmed the enhanced performance of the authentication system.
    • The system demonstrates increased reliability in verifying authorized individuals despite potential fingerprint shifts.

    Conclusions:

    • The optimized core detection and re-input strategy significantly enhance the robustness of the smart card authentication system.
    • The improved false rejection rate contributes to more secure and user-friendly biometric authentication.
    • This research offers a practical solution for real-world biometric security applications.