Iris Recognition System using Polar Spline RANSAC based on Total Variation Model
Keywords:Iris recognition, Segmentation, image processing, Biometric identification, Polar Spline RANSAC, Total Variation Model
A biometric system allows an individual to be automatic identification using a distinguishing or single feature possessed by the person. The biometric system of identification available which is regarded as the most accurate and reliable known is iris recognition. In this paper, we discuss the strategies used to construct an Iris Recognition System, as well as an analysis of our findings. To locate the limits of the iris in the digital image of the human eye, we used an integration procedure that incorporated both a Polar Spline RANSAC and a Total Variation Model. Predictable patterns of an individual's iris are retrieved as a feature vector using Daugman's rubber sheet model and the Gabor filter. The quantified values are then compared using the Hamming Distance operator to see whether the two irises are really the same. Experiments demonstrated that the accuracy of the recommended strategy for photographs acquired in uncooperative situations is either superior to or equivalent to other ways provided in the literature.
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