Fingerprint based Gender Identification using Discrete Wavelet Transform and Gabor Filters

Abstract

Usage of biometrics in day today life is becoming inevitable. Fingerprints are one of the most notable biometric technologies and are considered legitimate evidence all over the world. Research carried out so for on gender identification techniques is from the face image with relatively more complex resulting in high accuracy. Fingerprint trait can also be used for estimation of gender information and classification. In the proposed work DWT and Gabor based features are used to extract the gender information from fingerprints for classification of male and female. For experimentation fingerprint images of 74 persons with different age and gender is collected and stored in database. Accordingly in the experimental observations an 85% and 87% classification rate is achieved and by using Gabor filters the top-class accuracy of 97% is obtained.