Gender verification system based on JADE-ICA: Application to biometric identification system

Abstract

Biometric systems are one of the hottest topics in technology research due their possibilities. An example of these systems may be able to differ between male and female humans. This is called a gender classifier, and it finds applications in areas such as security, marketing, or even as a reinforcement of other biometric systems like face identification. In this work, a gender classifier system is modelled. The system implements two different feature extraction algorithms based on Independent Component Analysis (ICA). On the other hand, Support Vector Machines (SVM) is used as the classifier method. Finally, after 50 runs and 350 independent samples tested in each run, results give rise to an average of 82.40% of success working with Joint Approximate Diagonalization of Eigen-matrices (JADE) ICA and SVM. Moreover, significant differences between JADE-ICA and Fast-ICA algorithms have been pointed out, not only in terms of success rate, but also in stability.