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 language | English (Ireland) |
|---|---|
| Title of host publication | A Deep Learning approach to Segmentation of Distorted Iris regions in Head-Mounted Displays |
| Number of pages | 5 |
| Publication status | Published - 1 Feb 2018 |
Authors (Note for portal: view the doc link for the full list of authors)
- Authors
- Varkarakis, V,Bazrafkan, S,Corcoran, P,