Fingerprint based Gender Identification using Discrete Wavelet Transform and Gabor Filters
Author(s) -
Shivanand S. Gornale,
Abhijit Patil,
C. Veersheety
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016911794
Subject(s) - computer science , fingerprint (computing) , identification (biology) , pattern recognition (psychology) , artificial intelligence , gabor transform , discrete wavelet transform , gabor wavelet , gabor filter , computer vision , wavelet , wavelet transform , image (mathematics) , filter (signal processing) , time–frequency analysis , botany , biology
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. Keywordsidentification, fingerprint, DWT, QDA, LDA, Gabor filters.
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