Predicting Gender Using Iris Images
Arpit Bansal, Ravinder Agarwal · 2014
Among various biometric authentication systems iris recognition system is considered to be more accurate and reliable. The main objective of these systems is to identify the user as an authentic or an imposter. These systems does not reveal about imposter’s gender or ethnicity. Majority of practices for gender classification utilize facial information. Very few references in the literature reported the identification of human attributes such as gender with the help of iris images. In this paper gender has been identified using iris images. Feature vector from an iris image is created by combining statistical features and texture features using wavelets. A gender prediction model using Support Vector Machine (SVM) has been developed and an accuracy of 85.68% has been achieved.