Fingerprint Gender Classification using Wavelet Transform and Singular Value Decomposition
A novel method of gender Classification from fingerprint is proposed based on discrete wavelet transform (DWT) and singular value decomposition (SVD). The classification is achieved by extracting the energy computed from all the sub-bands of DWT combined with the spatial features of non-zero singular values obtained from the SVD of fingerprint images. K nearest neighbor (KNN) used as a classifier. This method is experimented with the internal database of 2200 fingerprints finger prints in which 1320 were male fingerprints and 880 were female fingerprints. Finger-wise gender classification is achieved which is 94.32% for the left hand little fingers of female persons and 95.46% for the left hand index finger of male persons. Gender classification for any finger of male persons tested is attained as 91.67% and 84.69% for female persons respectively. Overall classification rate is 88.28% has been achieved.
Keywords: Gender Classification, Fingerprint, Discrete Wavelet Transform, Singular Value Decomposition, k nearest neighbor
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ABOUT THE AUTHORS
Gnanasivam P
P. Gnanasivam received his A.M.I.E in electronics and communication engineering from Institution of Engineers (India) in 1989 and M.E in Applied Electronics from the Anna University, India in 2003. He is currently working towards the Ph.D. degree in the Department of Electronics and Communication Engineering, Anna University, India. His research interests include Pattern recognition, Image processing, Biometrics and Embedded system.
Muttan S
Center for Medical Electronics, Department of ECE, College of Engineering, Anna University, Chennai, Tamilnadu-600025, India
Gnanasivam P
P. Gnanasivam received his A.M.I.E in electronics and communication engineering from Institution of Engineers (India) in 1989 and M.E in Applied Electronics from the Anna University, India in 2003. He is currently working towards the Ph.D. degree in the Department of Electronics and Communication Engineering, Anna University, India. His research interests include Pattern recognition, Image processing, Biometrics and Embedded system.
Muttan S
Center for Medical Electronics, Department of ECE, College of Engineering, Anna University, Chennai, Tamilnadu-600025, India
