@inproceedings{859684b1afb546efbb88610483a09616,
title = "Challenging eye segmentation using Triplet Markov spatial models",
abstract = "We present a novel implementation of Triplet Markov Fields (TMF) for the unsupervised region segmentation of challenging eye images, representative of the iris recognition context. Results confirm the interest of such models over the classical Hidden Markov Field (HMF) and traditional gradient-based approaches for iris and periocular detection. We show that the precision of the resulting normalization circles is largely improved through the use of such TMF model as well as the quality of the image segmentation, despite of various degradations. These results are promising for further integration of TMF approaches in iris verification systems.",
keywords = "Biometry, Iris, Markov Model, Segmentation, Triplet Markov Fields",
author = "Dalila Benboudjema and Nadia Othman and Bernadette Dorizzi and Wojciech Pieczynski",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6637989",
language = "English",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "1927--1931",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}