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Communication Dans Un Congrès Année : 2013

Improving video-based iris recognition via local quality weighted super resolution

Résumé

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

Dates et versions

hal-01275240 , version 1 (17-02-2016)

Identifiants

Citer

Nadia Othman, Nesma Houmani, Bernadette Dorizzi. Improving video-based iris recognition via local quality weighted super resolution. ICPRAM 2013 : 2nd International Conference on Pattern Recognition Applications and Methods, Feb 2013, Barcelone, Spain. pp.623 - 629, ⟨10.5220/0004342306230629⟩. ⟨hal-01275240⟩
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