Texture feature based fingerprint recognition for low quality images

Win, Zin Mar; Sein, Myint Myint

doi:10.1109/mhs.2011.6102204

Cited by 14 publications

(4 citation statements)

References 19 publications

(13 reference statements)

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“…As an alternative, biometric approaches have recently received much attention for individual identification. The typical biometric technologies currently available are fingerprint identification [ 1 , 2 , 3 ], face identification [ 4 , 5 ], and iris identification [ 6 ]. Among various biometric information generated by the human body, ECG signals, which monitor the electrical heart activity, are another possible solution for individual identification.…”

Section: Introductionmentioning

confidence: 99%

Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

Lee

Kim

2018

Sensors

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The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.

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Section: Introductionmentioning

confidence: 99%

Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

Lee

Kim

2018

Sensors

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“…The Fingerprint matching performance is analyzed with FAR, FRR, EER (Equal Error Rate), GAR (Genuine Accept Rate). Zin Mar Win et al [5] use a correlation based Fingerprint method. The method uses Gabor filters for Fingerprint feature extraction.…”

Section: A Matching Techniques and Recognition Methodsmentioning

confidence: 99%

A Review on Biometrics Authentication System Using Fingerprint

Sureshbabu

Sakthivadivu

2019

AJCST

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Technology based on Biometric identification and verification is one leading research area. It deals with the concept analyzing the human body characteristics through Biometric devices for various authentications process. There are many Biometric authentication systems are available for verification process. This paper discusses the role of Fingerprint authentication. FP recognition is highly used biometric technique, because of abundance sources (i.e. ten fingers) availability for collecting data. Discussion on Fingerprint matching techniques, recognition methods and their performance analysis are made in the paper.

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“…Zin Mar Win et al [7] use a correlation based FR system. The scheme uses Gabor filters for FP feature extraction.…”

Section: A Matching Techniques and Recognition Methodsmentioning

confidence: 99%

A Study of Biometric Approach Using Fingerprint Recognition

Subban¹,

Mankame²

2013

LNSE

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Abstract-Fingerprint (FP) serves to identify that the person authenticating is who he/she claims to be. FP identification is popular biometric technique due to easiness in acquiring, availability of plenty sources (i.e. ten fingers) for collecting data and their established use. This paper summarizes the research work carried out in FP matching techniques, recognition methods and their performance analysis.

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Texture feature based fingerprint recognition for low quality images

Cited by 14 publications

References 19 publications

Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

Individual Biometric Identification Using Multi-Cycle Electrocardiographic Waveform Patterns

A Review on Biometrics Authentication System Using Fingerprint

A Study of Biometric Approach Using Fingerprint Recognition

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