Recognition of unideal iris images using region-based active contour model and game theory

We process the unideal iris images that are acquired in an unconstrained situation and are affected severely by gaze deviations, eyelid and eyelash occlusions, non uniform intensities, motion blurs, reflections, etc. The proposed unideal iris recognition algorithm has two novelties as compared to the previous works; firstly, we propose to deploy a region-based active contour model to segment an unideal iris image with intensity inhomogeneity; Secondly, an iterative algorithm, called the Modified Contribution- Selection Algorithm (MCSA), is used in the context of coalitional game theory to select a subset of informative features without compromising the recognition rate. The verification performance of the proposed scheme is validated using the UBIRIS Version 1, the ICE 2005, and the WVU Unideal datasets.