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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 C=O, C=N, and C=C occur between 1600–1850 cm−1.
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Finger vein recognition based on a personalized best bit map.

Gongping Yang¹, Xiaoming Xi, Yilong Yin

¹School of Computer Science and Technology, Shandong University, Jinan 250101, China. gpyang@sdu.edu.cn

Sensors (Basel, Switzerland)

|March 23, 2012

Summary

This study introduces a personalized best bit map (PBBM) for finger vein recognition. The PBBM method enhances accuracy and reliability in biometric identification using finger vein patterns.

Keywords:

Hamming distance finger vein recognition general framework local binary pattern personalized best bit map

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Area of Science:

Biometrics
Computer Science
Pattern Recognition

Background:

Finger vein patterns are emerging as a reliable biometric identifier.
Existing methods often rely on local binary patterns for feature extraction.

Purpose of the Study:

To propose a novel finger vein recognition method using a personalized best bit map (PBBM).
To enhance the accuracy, robustness, and reliability of biometric identification systems.

Main Methods:

Development of the personalized best bit map (PBBM) concept and its generation algorithm.
Implementation of a finger vein recognition framework including preprocessing, feature extraction, and matching.
Utilizing selected 'best bits' from local binary patterns for improved matching.

Main Results:

The proposed PBBM method demonstrated superior performance compared to existing approaches.
Experimental results confirmed high robustness and reliability of the PBBM-based recognition.
The PBBM framework proved effective for binary pattern-based recognition tasks.

Conclusions:

The personalized best bit map (PBBM) offers a significant advancement in finger vein recognition technology.
PBBM provides a robust and reliable solution for biometric identification.
The PBBM approach is adaptable for broader applications in binary pattern recognition.