Lookup NU author(s): sinan Alkassar,
Dr Wai Lok Woo,
Professor Satnam Dlay,
Professor Jonathon Chambers
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Sclera recognition has received attention recently due to the distinctive features extracted from blood vessels within the sclera. However, uncontrolled human pose, multiple iris gaze directions, different eye image capturing distance and variation in lighting conditions lead to many challenges in sclera recognition. Therefore, we propose an enhanced system for sclera recognition with visible-wavelength eye images captured in unconstrained conditions. The proposed segmentation algorithm fuses multiple color space skin classifiers to overcome the noise factors introduced through acquiring sclera images such, as motion, blur; gaze and rotation. We also propose a blood vessel enhancement and feature extraction method which we denote as complex-sclera features to increase the adaptability to noisy blood vessel deformations. The proposed system is evaluated using UBIRIS.v1, UBIRIS.v2 and UTIRIS databases and the results are promising in terms of accuracy and suitability in real-time applications due to low processing times.
Author(s): Alkassar S, Woo WL, Dlay SS, Chambers JA
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 9th International Conference on Biometrics (ICB)
Year of Conference: 2016
Online publication date: 25/08/2016
Acceptance date: 01/01/1900
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