Prediction of gender characteristic

Prediction of gender characteristics from iris images has been investigated
and some successful results have been reported in the literature, but without considering performance for different iris features and classifiers. This paper investigates for
the first time an approach to gender prediction from iris images using different types
of features (including a small number of very simple geometric features, texture features and a combination of geometric and texture features) and a more versatile and
intelligent classifier structure. Our proposed approaches can achieve gender prediction
accuracies of up to 90% in the BioSecure Database