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Reseach Article

A Study on Various Methods based on Gender Classification through Fingerprints

Published on May 2015 by Suman Sahu, A Prabhakar Rao
National Conference Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
Foundation of Computer Science USA
ACEWRM2015 - Number 2
May 2015
Authors: Suman Sahu, A Prabhakar Rao
d06f19e9-fde0-4501-bdcf-3c3b50d36f0f

Suman Sahu, A Prabhakar Rao . A Study on Various Methods based on Gender Classification through Fingerprints. National Conference Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering. ACEWRM2015, 2 (May 2015), 27-31.

@article{
author = { Suman Sahu, A Prabhakar Rao },
title = { A Study on Various Methods based on Gender Classification through Fingerprints },
journal = { National Conference Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering },
issue_date = { May 2015 },
volume = { ACEWRM2015 },
number = { 2 },
month = { May },
year = { 2015 },
issn = 0975-8887,
pages = { 27-31 },
numpages = 5,
url = { /proceedings/acewrm2015/number2/20908-6034/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
%A Suman Sahu
%A A Prabhakar Rao
%T A Study on Various Methods based on Gender Classification through Fingerprints
%J National Conference Potential Research Avenues and Future Opportunities in Electrical and Instrumentation Engineering
%@ 0975-8887
%V ACEWRM2015
%N 2
%P 27-31
%D 2015
%I International Journal of Computer Applications
Abstract

This paper is proposed of determining the gender through fingerprints. Finger prints verification is one of the most reliable personal identification method and it plays a very important role in forensic application like criminal investigation. Finger prints has been used as a biometric for the gender identification because of its unique nature and do not change throughout the life of an individual. Estimating the gender of fingerprints is an emerging field and many methods using the fingerprint physical features like the ridge count and the ridge thickness have been used so far. This study highlights various ridge and minutiae related methods which are based on the basis of some features of finger such as ridge count, ridge density, ridge to valley area ratio(RVA) and ridge width for fingerprint identification and gender classification through fingerprints. Different algorithms have analysed for finger prints based gender classification in this paper such as Singular Value Decomposition(SVD), Principle ComponentAnalysis(PCA),Neural Network(NN),Adaptive Resonance Theory(ART),Fuzzy- C Means (FCM), Linear Discriminate Analysis (LDA), k-nearest neighbour (k-NN) classifier . These algorithms provide different recognition rates and performances hence their comparative study can prove useful for the designing of an efficient and robust fingerprint identification system allowing its successful application on security authentication. To classify a given fingerprint image as male or female, we extracted the most significant features such as RVA and Ridge density from the existing database. These features were then used to train the ANFIS classifier. The experimental results showed that the proposed system can be used as a prime candidate in forensic anthropology with a higher accuracy than NN and Fuzzy individually.

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Index Terms

Computer Science
Information Sciences

Keywords

K-nn Classifier Rva Lda Fcm Neural Network Art Pca.