Adapting Starburst for Elliptical Iris Segmentation

Fitting an ellipse to the iris boundaries accounts for the projective distortions present in off-axis images of the eye and provides the contour fitting necessary for the dimensionless mapping used in leading iris recognition algorithms. Previous iris segmentation efforts have either focused on fitting circles to pupillary and limbic boundaries or assigning labels to image pixels. This paper approaches the iris segmentation problem by adapting the starburst algorithm to locate pupillary and limbic feature pixels used to fit a pair of ellipses. The approach is evaluated by comparing the fits to ground truth. Two metrics are used in the evaluation, the first based on the algebraic distance between ellipses, the second based on ellipse chamfer images. Results are compared to segmentations produced by ND_IRIS over randomly selected images from the iris challenge evaluation database. Statistical evidence shows significant improvement of starburst's elliptical fits over the circular fits on which ND_IRIS relies.

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