NDLI: Study on enhancing the accuracy of fingerprint recognition system

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Study on enhancing the accuracy of fingerprint recognition system

Content Provider	Scilit
Author	Abhishek Gautam, Ajai Kumar
Copyright Year	2021
Description	With the rapid advancements of the technology everyone is socially connected with each other by means of internet. This will also give rise to the problem of theft of each other identities whether there is a swipe card transaction, border crossing, time attendance, driving license, personal computers, personnel digital assistants to access the confidential files. So unique impression of each individual which can't be duplicated is thus required. Therefore in order to avoid such kind of theft, bio-metrics plays a dominant role, which include face recognition, iris recognition and fingerprint recognition among all of these fingerprint provides high level of abstraction to the user security. In this paper we have done comparison of various image enhancements methods and discussed classification of fingerprint recognition with some machine learning techniques like Random Forest, SVM, Naive Bayes, Radial Basis Function network algorithms along with some deep learning algorithms like Convolutional neural network. Index Terms—Fingerprint Recognition, Random Forest, SVM, Naive bayes, Radial Basis Function (RBF), Convolutional Neural Network(CNN) Book Name: Recent Trends in Communication and Electronics
Related Links	https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003193838-34&type=chapterpdf
Ending Page	183
Page Count	5
Starting Page	179
DOI	10.1201/9781003193838-34
Language	English
Publisher	Informa UK Limited
Publisher Date	2021-06-19
Access Restriction	Open
Subject Keyword	Book Name: Recent Trends in Communication and Electronics Hardware and Architecturee Neural Fingerprint Recognition Function Radial Naive Bayes Convolutional Svm
Content Type	Text
Resource Type	Chapter

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