Segmentation of Unideal Iris Images Using Game Theory

Robust localization of inner/outer boundary from an iris image plays an important role in iris recognition. However, the conventional iris/pupil localization methods using the region-based segmentation or the gradient-based boundary finding are often hampered by non-linear deformations, pupil dilations, head rotations, motion blurs, reflections, non-uniform intensities, low image contrast, camera angles and diffusions, and presence of eyelids and eyelashes. The novelty of this research effort is that we apply a parallel game-theoretic decision making procedure by using the modified Chakra borty and Duncan's algorithm, which integrates the region-based segmentation and gradient-based boundary finding methods and fuses the complementary strengths of each of these individual methods. This integrated scheme forms a unified approach, which is robust to noise and poor localization.