Three-phase Pupil Localization Method in Non-ideal Eye Images

摘要

Pupil localization is a very important preprocessing step in many real applications. Accurate and robust pupil localization in non-ideal eye images is a challenging task. A detailed method of pupil localization in non-ideal eye images is proposed. This method is implemented in three main phases: first, segment the rough pupil region based on Gaussian Mixture Model; then modify the rough segmentation result using morphological method to minimize the influence of some disturbing factors; last estimate the pupil parameters based on minimizing the least square error. The proposed method is first tested on CASIA iris image dataset, and then on our self-captured iris dataset which contains a wider variety of iris images. Experiments show that the proposed method can perform well for nonideal eye images of various qualities.