Author : Mohamed Ismail Roushdy
CoAuthors : Manar Ramzy Dronky ,Wael Khalifa
Source : 2019 14th International Conference on Computer Engineering and Systems (ICCES)
Date of Publication : 12/2019
Abstract : Applying iris recognition systems in many sensitive
security areas highlights the importance of developing liveness
detection methods. These methods read the users physiological
signs of life to verify if the iris pattern acquired for identification
is fake or real. This paper explores the results of BSIF for solving
the problem of iris liveness detection to combat presentation
attacks. Four public datasets representing printed, plastic,
synthetic and contact lens attacks were used for method evaluation
in both scenarios segmented and unsegmented eye images. The
results have showed that BSIF can efficiently detect plastic and
synthetic attacks without segmentation with correct classification
rate of 100%. In addition, unsegmented eye images achieved better
results in detecting print attack on the tested datasets. While,
segmentation is still required in the most challenging attack which
is by contact lens.
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