Fast and accurate iris segmentation based on linear basis function and RANSAC
Kai Wang, Yuntao Qian · 2011
Iris segmentation is a component of iris recognition system, and noncircular iris is hard to segment accurately. This paper presents an iris segmentation algorithm using linear basis function and RANSAC (Random SAmple Consensus) which iterately derives fine iris boundary curves from coarse iris boundary points. The algorithm consists of three steps. In step 1, coarse center and radius of iris are found using IDO (Integro Differential Operators); in step 2, coarse iris boundary points are located, and then a linear basis function model is constructed to derive coarse iris boundary curves from the boundary points; and in step 3, a RANSAC method is applied to refine the iris boundary curves. The proposed algorithm is tested on two datasets CASIA-Iris V3-Interval and IITD v1.0 and shows the effectiveness comparing with some popular algorithms.