Iris Segmentation Based upon Linear Basis Function Model
Yuntao Qian · Guangdian gongcheng · 2011
To improve accuracy of non-circular iris segmentation,an iris segmentation algorithm based on linear basis function model is proposed.The proposed algorithm regards iris segmentation problem as a machine learning problem which derives iris boundary curve from iris boundary points.First,boundary points are located by coarse segmentation.Second,a linear basis function model is constructed to derive boundary curve from boundary points,thus the segmentation is complete.Compared with traditional iris segmentation algorithms,the proposed method locates non-circular iris with high accuracy,with the expense of a few more time.Experiment results on the dataset of CASIA-3.0 IRIS-Interval reveal that the accuracy of proposed method is 99.92%,and the time cost is 1ms more,which is capable for state-of-the-art iris recognition systems.