Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
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.

References
  1. Rijo Jackson Tom, T. Arulkumaran , " Fingerprint Based Gender Classification Using 2D Discrete Wavelet Transforms and Principal Component Analysis ". International Journal of Engineering Trends and Technology, Volume 4 Issue 2, 2013.
  2. P. Gnanasivam & Dr. S. Muttan " Estimation of Age Through Fingerprints Using Wavelet Transform and Singular Value Decomposition" International Journal of Biometrics and Bioinformatics (IJBB), Volume (6) : Issue (2) : pp 58 - 67. 2012.
  3. E. O. Omidiora, O. Ojo, N. A. Yekini, T. O. Tubi "Analysis, design and implementation of human fingerprint patterns system "towards age & gender determination, ridge thickness to valley thickness ratio (RTVTR) & ridge count on gender detection" International Journal of Advanced Research in Artificial Intelligence, Vol. 1, No. 2 , pp 57 - 63, 2012.
  4. Ritu Kaur and Susmita Ghosh Mazumdar, "Fingerprint Based Gender Identification using Frequency Domain Analysis". International Journal of Advances in Engineering & Technology, March 2012. ©IJAET ISSN: 2231 – 1963.
  5. Dr. Prateek Rastogi, Ms. Keerthi R Pillai "A study of fingerprints in relation to gender and blood group" J Indian Acad Forensic Med 2011 , 32(1), pp - 11 - 14 ISSN 0971 – 097.
  6. Ramanjit Kaur, Rakesh K. Garg "Determination Of Gender Differences From Fingerprint Ridg e Density In Two Northern Indian Populations" Problems of Forensic Sciences 2011, vol. LXXXV, 5 – 10.
  7. Manish Verma and Suneeta Agarwal. '' Fingerprint Based Male - Female Classification. '' in Proceedings of the international workshop on computational intelligence in security for information systems (CISIS'08), Genoa, Italy, 2008, pp. 251 – 257.
  8. Jen feng wang, et al, " Gender Determination using Fingertip Features". Internet Journal of Medical Update 2008 Jul - Dec;3(2):22 – 8.
  9. A. Badawi, M. Mahfouz, R. Tadross, and R. Jantz "Fingerprint - based gender classification" The International Conference on Image Processing, Computer Vision, and Pattern Recognition, June 2006.
  10. Acree, M. "Is there a gender difference in fin gerprint ridge density?" Forensic Science International 1999 May; 102 (1)
  11. Gajanan Pandurang Khetri , Satish L. Padme , Dinesh Ch Jain, Vrushsen P. Pawar "Fingerprint Pattern Recognition Using Back Propagation Algorithms" International Journal of Electronics and Computer Science Engineering. ISSN 2277-1956/V2N1-225-232
  12. Ravi Wadhwa,ManinderKaur, Dr. K. V. P. Singh "Age and Gender Determination from Finger Prints using RVA and dct Coefficients" IOSR Journal of Engineering (IOSRJEN) e-ISSN: 2250-3021, p-ISSN: 2278-8719 Vol. 3, Issue 8 (August. 2013), ||V5|| PP 05-09.
  13. S. S. Gornale, Geetha C D, Kruthi R "Analysis Of Fingerprint Image For Gender Classification Using Spatial And Frequency Domain Analysis" American International Journal of Research in Science, Technology, Engineering & Mathematics, 1(1), pp. 46-50, June-August, 2013.
  14. Marius Tico, EeroImmonen, Pauli Ramo, Pauli Kuosmanen, and Jukka Saarinen "Fingerprint Recognition Using Wavelet Features" IEEE.
  15. Ahmed Badawi, Mohamed Mahfouz, RimonTadross, Richard Jantz, "Fingerprint-Based Gender Classification. " Biomedical Engineering department, University of Tennessee Knoxville. June 2006.
  16. Arun K. S. Sarath"A Machine Learning Approach for Fingerprint Based Gender Identification" 978-1-4244-9477-4/11/$26. 00 ©2011 IEEE
  17. Marius Tico, EeroImmonen, Pauli Ramo, Pauli Kuosmanen, and Jukka Saarinen "Fingerprint Recognition Using Wavelet Features" IEEE.
Index Terms

Computer Science
Information Sciences

Keywords

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