Use of Deep Learning Approach in Predicting the Gender using Fingerprints

Abstract

A fingerprint has been considered as one of the unique identities connected with every person. Fingerprints are imprints left by the papillary ridges at the tips of all fingers. Every human finger has a unique ridge arrangement that does not change as they get older. As a result, these are employed in forensics to identify suspects personally. The fingerprint ridge patterns of arches, loops, and whorls are compared to store data. Latest research studies have shown that the fingerprint data can be used for predicting the gender of the suspect. This made the forensic department do the first level of classification about the suspect at the basic level. This paper has a focus on predicting the gender and the age of the suspect. The training models have shown that the derived results have given better accuracy of 87% percent.