Pupil segmentation using Pulling & Pushing and BSOM neural network

Segmentation is a preliminary step for many computer vision systems. Several segmentation algorithms have been developed for different tasks. Here, we are interested in the pupil segmentation, an important procedure in iris recognition systems. In most of the pupil segmentation algorithms it is assumed that the pupil has a circular shape. These methods inaccurate identify pupil borders that do not have a circular shape. In iris recognition, the error caused by an imprecise segmentation can lead to poor recognition rates. In this paper we propose a new method for pupil segmentation based on the Pulling & Pushing method and a batch-SOM neural network in order to improve the segmentation. We tested the proposed method in the MMU1 and Casia V3 iris databases, obtaining accurate results.