A novel iris center localization based on circle fitting using radially sampled features

In this paper, we propose a novel iris center (IC) localization method. Given an eye region image, we first find an initial iris center and perform iterative circle fitting until the center of the circle converges on the final IC. In each iteration step, a certain number of feature points (FPs) are extracted from radial sectors defined around the IC, and then grouped into several clusters for circle fitting. Through the iteration, the circle center converges on the final IC. Experimental results on the public dataset GI4E show that the proposed method achieves the superior performance as compared with conventional ones.