Description

In this process, we speculate about the gender-related variations in vein patterns, and their effects on biometric verification performance. An analysis on the feasibility of recognizing male and female subject depending on their hand-vein patterns, and on the level of similarity characterizing the biometric templates extracted from male and female populations, The obtained experimental results show that the approach here proposed to perform gender recognition allows to reach an accuracy up to 95.83% on the public dataset.