Predicting and Classifying Gender from the Human Iris: A Survey on Recent Advances
Gugulethu Mabuza-Hocquet, Cnythia Hombakazi Ngejane, Samuel Lefophane · 2018
The prediction and classification of soft biometrics such as gender and ethnicity from iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a youthful and active research topic in iris biometrics. The large body of knowledge and research in iris biometrics has been focused on individual recognition and verification. Such research has been conducted with an aim of improving existing algorithms especially to deal with non ideal iris images. So far, researchers in the field of iris biometrics have proposed various methods of classifying the gender of individuals from iris images. The aim of this paper is to amalgamate most of the work that has been done by researchers, through delving and comparing the different techniques, algorithms and results achieved over the last decade. This work only documents the research that has been published specifically in the field of iris biometrics.