Comparing and Improving Algorithms for Iris Recognition

The iris has been proposed as a reliable means of biometric identification. The importance of the iris as a unique identifier is predicated on the assumption that the iris is stable throughout a person´s life. This does not take into account the fact that the iris changes in response to a number of external factors including medication, disease, surgery and age and is part of a dynamic optical system that alters with light levels and focussing distance. What is required is a means of identifying the features in the iris which do not alter over time from those that change in response to external factors. Iris segmentation issues and the effects of pupil dilation in identification are examined in this study using existing iris recognition algorithms and a series of images captured from three subjects. A technique that enhances segmentation is presented and discussed.