Accurate iris segmentation based on novel reflection and eyelash detection model

W.K. Kong, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

184 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2001
Number of pages4
Publication statusPublished - 2001

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