A Framework for Iris Localization based on Greedy Snake Model
M. Ganesh · Solid State Technology · 2020
This paper proposes a framework for iris localization with greedy snake model to accuratelyextract iris region and compensate for the accuracy problem caused by the non-standard circlecharacteristics of the iris. Initially upper eyelashes are detected and removed with mathematicalcomputational basis operators within a windowed eye region. In the proposed scheme, the non circularpupil contour is detected in an iterative fashion with a novel edge based two stage greedy snake model. Inthe first stage, the pupil-iris edge is coarsely located with mathematical computational gradient detector andin the second stage, the precise pupil contour is detected with greedy snake in which the contour isinitialized within the pupil and deformed into new shape in response to the two controlling force models,introduced as internal and external forces to properly activate the contour. The image gradient and thecurvature are utilized together to determine the speed and direction of the contour deformation,while for thelocalization of limbus boundary vertical edges are detected between iris and sclera region with horizontalpolynomials coefficient. Then the precise limbus boundary is localized from the two annulus sector areawith the detection of radial boundary points in a sequence along angular directions within the specifiedprojection curve radiating from pupil center. The experimental results with standard CASIA database showthat the proposed scheme is robust in finding exact noncircular pupil, limbus boundary and eyelids.