Gender classification from fingerprint ridge count and fingertip size using optimal score assignment

Abstract

Information on the gender of a person plays a vital role in crime investigation, authentication and statistical report on the visitors. In this work, fingerprint ridge count and fingertip size are used as the parameters for automatic gender classification. As a novel method, the optimal score assignment (OSA) method is proposed to classify gender. An optimal score is calculated for male and female from the internally collected fingerprint database. Fingerprints are collected under four age groups and all the fingers are scanned. For the fingerprint image ‘I’ for which gender is to be identified, scores are assigned for ridge count and fingertip assuming that the given image is male. A similar calculation is made assuming that the given image is female. Comparing both values, gender is declared. The maximum success rate attained is 88.41% for the age group 18–25 years and a good success rate of 90.11% is achieved for the right hand ring finger. Performance evaluation is made with the earlier findings of the author and other methods.