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Research Article

JCR. 2020; 7(13): 2768-2773


A SHORT REVIEW ON MACHINE LEARNING TECHNIQUES USED FOR FINGERPRINT RECOGNITION

Jay Kant Pratap Singh Yadav, Zainual Abdin Jaffery, Laxman Singh.

Abstract
In all biometric traits, a fingerprint is considered as a foremost trait due to its high security level, reliability, universality, uniqueness, robustness, low costs, and user convenience. Due to the high level security and affordability, there is a large demand of deployment of fingerprint recognition systems which also arising lot of challenges including enhancement, pre-processing, features extraction and selection, features matching and classification of fingerprints. These challenges can be solved by machine learning techniques in nontraditional manner. In this paper, we present a short review of machine learning methods to rectify some fingerprint recognition systems challenges. This review also provides directions for using these machine learning algorithms on other biometric traits and developing new algorithms based on machine learning for fingerprint recognition systems in the near future.

Key words: Biometrics, Fingerprint, SVM, Genetic Algorithm, Artificial Neural Network, Convolution Neural Network



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The articles in Bibliomed are open access articles licensed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
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