Accurate iris segmentation based on novel reflection and eyelash detection model

In this paper, we propose a novel noise detection model for accurate segmentation of an iris. Eyelash, eyelid and reflection are three main noises. Eyelid had been solved by traditional eye model; however, eyelash and reflection do not been regarded. To determinate a pixel in an eyelash, our model follows the three criterions: 1) separable eyelash condition, 2) non-informative condition and 3) connective criterion. The first and second condition handle separable and multiple eyelashes respectively. The last criterion avoids misclassification of strong iris texture as a single and separable eyelash. For reflection, strong reflection points are detected by a threshold and the weak reflection points around the strong points are determined by connective criterion and statistical test. A number of images are selected to evaluate the accuracy and necessity of our noise detection model and the results are encouraging.