Improving Video-based Iris Recognition Via Local Quality Weighted Super Resolution

Nadia Othman, Nesma Houmani, Bernadette Dorizzi

Abstract

In this paper we address the problem of iris recognition at a distance and on the move. We introduce two novel quality measures, one computed Globally (GQ) and the other Locally (LQ), for fusing at the pixel level the frames (after a bilinear interpolation step) extracted from the video of a given person. These measures derive from a local GMM probabilistic characterization of good quality iris texture. Experiments performed on the MBGC portal database show a superiority of our approach compared to score-based or average image-based fusion methods. Moreover, we show that the LQ-based fusion outperforms the GQ-based fusion with a relative improvement of 4.79% at the Equal Error Rate functioning point.

References

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Paper Citation


in Harvard Style

Othman N., Houmani N. and Dorizzi B. (2013). Improving Video-based Iris Recognition Via Local Quality Weighted Super Resolution . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013) ISBN 978-989-8565-41-9, pages 623-629. DOI: 10.5220/0004342306230629


in Bibtex Style

@conference{btsa13,
author={Nadia Othman and Nesma Houmani and Bernadette Dorizzi},
title={Improving Video-based Iris Recognition Via Local Quality Weighted Super Resolution},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)},
year={2013},
pages={623-629},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004342306230629},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)
TI - Improving Video-based Iris Recognition Via Local Quality Weighted Super Resolution
SN - 978-989-8565-41-9
AU - Othman N.
AU - Houmani N.
AU - Dorizzi B.
PY - 2013
SP - 623
EP - 629
DO - 10.5220/0004342306230629