A Deep Learning approach to Segmentation of Distorted Iris regions in Head-Mounted Displays

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Abstract

In this paper, we consider the next generation of wearable AR VR display glasses and the challenges of personal authentication on such devices. The use of iris authentication as a mean of creating a seamless biometric link between the user and his personal data offers a viable approach, but due to the likely location of user-facing cameras there are some challenges in achieving an accurate segmentation of the iris. In this paper, a deep neural network was trained to accurately segment distorted iris regions. An appropriate augmentation method is presented to generate the distorted iris dataset used for training from publicly available frontal iris datasets. The proposed method shows promising results in segmenting off-axis iris images in unconstrained conditions.
Original languageEnglish (Ireland)
Title of host publication2018 IEEE GAMES, ENTERTAINMENT, MEDIA CONFERENCE (GEM)
PublisherIEEE
Number of pages4
Publication statusPublished - 1 Jan 2018

Authors (Note for portal: view the doc link for the full list of authors)

  • Authors
  • Varkarakis, V;Bazrafkan, S;Corcoran, P

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