Fusion of Fingerprint and Age Biometric for Gender Classification Using Frequency and Texture Analysis

Abstract

Classification of gender from fingerprints is one of the important steps in forensic anthropology. This forensic anthropology is used to identify the gender of a criminal in order to minimize the suspects list of search. A very few researcher have worked on gender classification using fingerprints and have gain the competitive results. In this work we are trying to fuse the fingerprint and age biometrics for gender classification. The real fingerprints were collected from different age groups such as 15-20 years and 20-60 years of the rural and urban people. According to this experimental observation soft biometric information can be used significantly to improve the recognition performance of biometric system. The overall performance of the proposed method is found to be satisfactory and more competitive. KEYWORDS Gender classification, frequency domain, texture analysis, soft biometrics and hard biometrics traits.