Gender classification and age estimation using fingerprint and ear features

Abstract

The problem of gender classification has been done by a few newlineauthors using fingerprint face voice and gait However this area has not newlinebeen studied extensively In this thesis a novel technique Optimal Score newlineAssignment OSA method is adopted for gender classification using newlinefingerprints The fingerprint friction ridge count ridge width and the fingertip newlinesize have been taken as features for the identification of gender By OSA newlinemethod the frequency of occurrence of particular value of each features are newlinecalculated for male and female Depends on the occurrence of particular value newlineof the features an optimal score is assigned individually for male and female of the fingerprint newline newline