Title :
Accurate iris localization using contour segments
Author :
Haiqing Li ; Zhenan Sun ; Tieniu Tan
Author_Institution :
Nat. Lab. of Pattern Recognition, Inst. of Autom., Beijing, China
Abstract :
We consider the problem of locating pupillary and limbic boundaries in iris images captured in non-cooperative environment. This work presents an efficient segment search algorithm, which takes advantage of shape information and learned iris boundary detectors, to enable exclusion of most noisy edges and extraction of genuine pupillary contour segments. Pupillary boundaries can then be accurately fitted as ellipses using the extracted segments. To locate limbic boundaries more stably, the shapes of pupillary boundaries constrain limbic boundary localization by adding inferred points during ellipse fitting. Extensive experiments on the challenging CASIA-Iris-Thousand iris image database demonstrate the effectiveness and efficiency of the proposed method.
Keywords :
curve fitting; edge detection; feature extraction; image segmentation; iris recognition; search problems; visual databases; CASIA-Iris-Thousand iris image database; accurate iris localization; ellipse fitting; genuine pupillary contour segment extraction; iris images; learned iris boundary detectors; limbic boundary localisation problem; noisy edge exclusion; noncooperative environment; pupillary boundary localisation problem; segment search algorithm; shape information; Detectors; Image edge detection; Image segmentation; Iris; Iris recognition; Noise; Shape;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4