A Study on Machine Learning Approach for Fingerprint Recognition System

Authors

  • Aayushi Tamrakar M. Tech. , Scholar Department of CSE, Technocrats Institute of Technology Bhopal, India
  • Neetesh Gupta Professor, Department of CSE, Technocrats Institute of Technology Bhopal, India

DOI:

https://doi.org/10.24113/ijoscience.v5i11.234

Keywords:

Biometric system; Fingerprint Recognition System; Minutiae; Reconstruction; Feature Extraction; Classification

Abstract

A biometric system is an evolving technology that is used in various fields like forensics, secured area and security system. Authentication system like fingerprint recognition is most commonly used biometric authentication system. Fingerprint method of identification is the oldest and widely used method of authentication used in biometrics. There are several reasons like displacement of finger during scanning, environmental conditions, behavior of user, etc., which causes the reduction in acceptance rate during fingerprint recognition. The result and accuracy of fingerprint recognition depends on the presence of valid minutiae. Fingerprint Recognition system designed uses various techniques in order to reduce the False Acceptance Rate (FAR) and False Rejection Rate (FRR) and to enhance the performance of the system. This paper reviews the fingerprint classification including feature extraction methods and learning models for proper classification to label different fingerprints. A comparative study of different recognition technique along with their limitations is also summarized and optimum approach is proposed which may enhance the performance of the system.

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References

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Published

11/19/2019

How to Cite

Tamrakar, A., & Gupta, N. (2019). A Study on Machine Learning Approach for Fingerprint Recognition System. SMART MOVES JOURNAL IJOSCIENCE, 5(11), 1–4. https://doi.org/10.24113/ijoscience.v5i11.234