Fingerprint Based Gender Classification Using 2D Discrete Wavelet Transforms and Principal Component Analysis
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2013 by IJETT Journal|
|Year of Publication : 2013|
|Authors : Rijo Jackson Tom , T.Arulkumaran|
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 (IJETT). V4(2):199-203 Feb 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Fingerprint evidence is undoubtedly the most reliable and accep table evidence till date in the court of law. Fingerprints are obtained at the site of crime and in many old monuments and in excavated things. Estimating the gender of fingerprints is an emerging field and many methods using the fingerprint physical feat ures like the ridge count and the ridge thickness have been used so far. Due to the immense potential of fingerprints as an effective method of identification an attempt has been made in the present work to analyze their correlation with gender of an indiv idual using frequency domain technique and a pattern recognition technique. The combined processing has provided better results. This paper aims in using 2D - Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) combined to classify gender using an obtained fingerprint. The minimum distance method was used as a classifier. Fingerprints of 200 males and 200 females belonging to the various age groups were taken for analysis. The experimental results show good for trained database. It was fo und that increasing the database population in each category improves the performance of the system.
 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
 Ritu Kaur and Susmita Ghosh Mazumdar “F ingerprint based gender identification using frequency domain analysis” International Journal of Advances in Engineering & Technology, Vol. 3, Issue 1 , pp. 295 - 299, March 2012
 Pankanti, S. Prabhakar, and A. K. Jain, “On the individuality of fi ngerprints,” I EEE Trans. Pattern Anal. Mach. Intell.”, vol. 24, no. 8, pp . 1010 – 1025, Aug. 2002.
 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 thicknes s 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
 http://www.unilorin.edu.ng/step - b/biometrics
 D. Maltoni, D. Maio, A. K. Jain, and S . Prabhakar, “Handbook of Fingerprint Recognition”, first ed., Springer , New York, 2003.
 Miroslav Kralik, Vladimir Novotny, “Epidermal Ridge Breadth: An Indicator of Age and Sex in Paleodermatoglyphics”, Variability and Evolution , Vol. 11, pp. 5 - 30, 2003.
 K. Thaiyalnayaki, S. A. Karim, P. V. Parmar, “Finger print Recogntion Using Discrete Wavelet Transform”, International Journal of Computer Applications ,pp.96 - 100,Vol.1,No.24, 2010
 A. K. Jain, S. Prabhakar and L. Hong, “A multichannel approach to fingerprin t classification,” IEEE Transactions on PAMI , pp. 48359, Vol.21, No.4, Apr.1999.
 M anish Verma and Suneeta Agarwal, “ Fingerprint Based Male - Female Classification.’’ in Proceedings of the International Workshop On Computational Intelligence i n Security f or Information Systems (CISIS’08), Genoa, Italy, 2008, pp.251 - 257.
 D.Maio and D.Maltoni, “Ridge - line density estimation in digital images,” in Proceedings of the 14th International Conference on Pattern Recognition ( ICPR), 1998, pp. 534 – 538