Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features

Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features

Background/Objective: A new algorithms of gender classification from fingerprint is proposed based on Acree 25mm2 square area. The classification is achieved by extracting the global features from fingerprint images which is Ridge Density, Ridge Thickness to Valley Thickness Ratio (RTVTR) and White...

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Bibliographic Details
Main Authors: Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad
Format: Article
Language:English
Published: Indian Society Of Education And Environment & Informatics Publishing Limited 2016
Subjects:
T Technology (General)
Online Access:http://eprints.utem.edu.my/id/eprint/17251/1/Multilayer%20Perceptron%20Neural%20Network%20In%20Classifying%20Gender%20Using%20Fingerprint%20Global%20Level%20Features.pdf
http://eprints.utem.edu.my/id/eprint/17251/
http://www.indjst.org/index.php/indjst/article/view/84889
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Institution: Universiti Teknikal Malaysia Melaka
Language: English

Internet

http://eprints.utem.edu.my/id/eprint/17251/1/Multilayer%20Perceptron%20Neural%20Network%20In%20Classifying%20Gender%20Using%20Fingerprint%20Global%20Level%20Features.pdf
http://eprints.utem.edu.my/id/eprint/17251/
http://www.indjst.org/index.php/indjst/article/view/84889

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