Iris Iterative Location Using Nonlinear Data Fitting and Cross-reference

The initial shape parameters were obtained first by using all edge pixels of iris, then discarding non-edge data iteratively according to the error of each subsequent fitting. New data were refined again and again until the average fitting error is under the defined threshold. Finally, the iris center and radius are decided accurately in a small scope by using standard Hough transform. Comparative simulation results show that the performance of speed and robustness is improved as compared to the existing methods.