A New Segmentation Method for Iris Recognition Using the Complex Inversion Map and Best-Fitting Curve

Abstract

Iris segmentation plays a vital role in automated iris recognition. In this paper, we presented a novel method for iris segmentation using a complex mapping and best-fitting curve procedure. We used an intensity threshold method to extract the rough region of the pupil. For the outer boundary a median filter with prewitt compass edge detector were used to localize the rough region of the outer boundary. By selecting the bottom point of the pupil, which is not usually occluded by the eyelids and eyelashes, as a reference point, two sets of intersecting points between the horizontal lines and pupil’s inner and outer boundaries were created. Each point set was map into a new complex domain using the complex inversion map function and the best-fitted line was found on the range. Exact inner and outer boundaries of the iris were found by remapping the best-fitted lines to original domain. We tested our proposed algorithm by implementing a ground truth method. Experimental results show that the proposed method has an encouraging performance.