Semantic Segmentation of Iris using U-Net in Deep Learning

Abstract

In the field of medicine, iris segmentation has become a great field of interest from the past few years. Iris segmentation is also largely used in iris recognition systems [3] which are extensively used in security control [1][2]. Here iris segmentation is done using semantic segmentation which is based on the U-Net architecture. The typical U-net architecture contains two paths- contracting path containing convolutional and pooling layers and the expanding path consists of transposed convolutional operations. The UBIRIS dataset is trained on the traditional U-Net model with some modifications according to the size of the images present in the UBIRIS dataset. The results obtained were very close to the ground truths and accuracy obtained is also appreciable.