  In this study the authors will look at the detection and segmentation of the
iris and its influence on the overall performance of the iris-biometric tool
chain. The authors will examine whether the segmentation accuracy, based on
conformance with a ground truth, can serve as a predictor for the overall
performance of the iris-biometric tool chain. That is: If the segmentation
accuracy is improved will this always improve the overall performance?
Furthermore, the authors will systematically evaluate the influence of
segmentation parameters, pupillary and limbic boundary and normalisation centre
(based on Daugman's rubbersheet model), on the rest of the iris-biometric tool
chain. The authors will investigate if accurately finding these parameters is
important and how consistency, that is, extracting the same exact region of the
iris during segmenting, influences the overall performance.
