Micro Stripes Analyses for Iris Presentation Attack Detection
- URL: http://arxiv.org/abs/2010.14850v2
- Date: Tue, 3 Nov 2020 11:56:53 GMT
- Title: Micro Stripes Analyses for Iris Presentation Attack Detection
- Authors: Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
- Abstract summary: We propose a framework to detect iris presentation attacks by extracting multiple micro-stripes of expanded normalized iris textures.
Our solution minimizes the confusion between textured (attack) and soft (bona fide) contact lens presentations.
- Score: 15.15287401843062
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Iris recognition systems are vulnerable to the presentation attacks, such as
textured contact lenses or printed images. In this paper, we propose a
lightweight framework to detect iris presentation attacks by extracting
multiple micro-stripes of expanded normalized iris textures. In this procedure,
a standard iris segmentation is modified. For our presentation attack detection
network to better model the classification problem, the segmented area is
processed to provide lower dimensional input segments and a higher number of
learning samples. Our proposed Micro Stripes Analyses (MSA) solution samples
the segmented areas as individual stripes. Then, the majority vote makes the
final classification decision of those micro-stripes. Experiments are
demonstrated on five databases, where two databases (IIITD-WVU and Notre Dame)
are from the LivDet-2017 Iris competition. An in-depth experimental evaluation
of this framework reveals a superior performance compared with state-of-the-art
algorithms. Moreover, our solution minimizes the confusion between textured
(attack) and soft (bona fide) contact lens presentations.
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