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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Non-ideal iris segmentation using graph cuts
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Shrinivas J. Pundlik, Electrical and Computer Engineering Department, USA
Damon L. Woodard, Image and Video Analysis Lab, School of Computing, Clemson University, SC 29634, USA
Stanley T. Birchfield, Electrical and Computer Engineering Department, USA
A non-ideal iris segmentation approach using graph cuts is presented. Unlike many existing algorithms for iris localization which extensively utilize eye geometry, the proposed approach is predominantly based on image intensities. In a step-wise procedure, first eyelashes are segmented from the input images using image texture, then the iris is segmented using grayscale information, followed by a post-processing step that utilizes eye geometry to refine the results. A preprocessing step removes specular reflections in the iris, and image gradients in a pixel neighborhood are used to compute texture. The image is modeled as a Markov random field, and a graph cut based energy minimization algorithm [2] is used to separate textured and untextured regions for eyelash segmentation, as well as to segment the pupil, iris, and background using pixel intensity values. The algorithm is automatic, unsupervised, and efficient at producing smooth segmentation regions on many non-ideal iris images. A comparison of the estimated iris region parameters with the ground truth data is provided.
Citation:
Shrinivas J. Pundlik, Damon L. Woodard, Stanley T. Birchfield, "Non-ideal iris segmentation using graph cuts," cvprw, pp.1-6, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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