Segmentation of the Iris and Pupil of the Human Eye in Images from an Infrared Camera

Abstract

Abstract Tasks related to the automation of medical data processing are becoming more urgent. Particular attention is paid to systems for monitoring and analyzing human physiological parameters. Such systems often use specialized sensors to capture biomedical images, such as infrared cameras. This article describes our study of the problem of segmenting the eye pupil and iris in images obtained using an infrared camera. In our work, we propose a proprietary deep neural network architecture with a novel loss function for learning to segment human ocular structures. We also present a segmentation dataset and perform a comparative analysis of different eye structure segmentation methods. Our proposed model outperforms other considered approaches and has demonstrated state-of-the-art results in segmentation of human ocular structures.