Abstract

This research proposes a method to detect alcohol consumption from a Near-Infra-Red (NIR) periocular eye images. The study focuses on determining the effect of external factors such as alcohol on the Central Nervous System (CNS). The goal is to analyse how this impacts on iris and pupil movements and if it is possible to capture these changes with a standard iris NIR camera. This paper proposes a novel Fused Capsule Network (F-CapsNet) to classify iris NIR images taken under alcohol consumption subjects. The results show the F-CapsNet algorithm can detect alcohol consumption in iris NIR images with an accuracy of 923% using half of parameters than the standard Capsule Network algorithm. This work is a step forward for developing an automatic system to estimate "Fitness for Duty" and prevent accidents due to alcohol consumption.