Supervised Neural Network and minimum distance features between singularities for fingerprint verification

Balti, Ala; Sayadi, Mounir; Fnaiech, Farhat

doi:10.1109/ssd.2013.6564001

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Cited by 3 publications

(1 citation statement)

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“…Balti et al [21], 2013 Avoid problems of geometric rotation and translations. Shan juan et al [22], 2013 Approaches OOCL level and shows lower error rate.…”

Section: Statistical Classifiermentioning

confidence: 99%

An Overview of Fingerprint Classification Techniques

2018

IJRASET

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“…Balti et al [21], 2013 Avoid problems of geometric rotation and translations. Shan juan et al [22], 2013 Approaches OOCL level and shows lower error rate.…”

Section: Statistical Classifiermentioning

confidence: 99%

An Overview of Fingerprint Classification Techniques

2018

IJRASET

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Selective review of fingerprint enhancement, classification and matching techniques

Patil

Zope²

2015

2015 IEEE Bombay Section Symposium (IBSS)

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Application of Machine Learning in Fingerprint Image Enhancement and Recognition: A Review

Singh¹,

Dixit²

2021

IJOSCIENCE

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Biometric characteristics helps to recognize an individual among others. Each individual has a unique biometric feature. So, an automated system is designed to recognize an individual. In today’s growing AI development, biometric recognition is applied in many security systems. One of oldest and widely used authentic biometric methodology is fingerprint recognition. Many fingerprint recognition algorithms are designed and developed in order to reduce error rate and to improve accuracy. In this paper, a comprehensive review is presented on various techniques used for fingerprint recognition system along with their performance and their limitations. The purpose of this paper is to review various recent work on the fingerprint recognition system, to explain step by step the steps for recognizing fingerprints, and to provide summaries of the fingerprint databases with functionality

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Supervised Neural Network and minimum distance features between singularities for fingerprint verification

Cited by 3 publications

References 15 publications

An Overview of Fingerprint Classification Techniques

An Overview of Fingerprint Classification Techniques

Selective review of fingerprint enhancement, classification and matching techniques

Application of Machine Learning in Fingerprint Image Enhancement and Recognition: A Review

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