Authors:
Ana F. Sequeira
1
;
Juliano Murari
2
and
Jaime S. Cardoso
1
Affiliations:
1
INESC TEC and Universidade do Porto, Portugal
;
2
Universidade Federal de S. Paulo, Brazil
Keyword(s):
Biometrics, Iris, Liveness Detection, Fake Database, Handheld Device.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Mobile Imaging
Abstract:
Biometric systems are vulnerable to different kinds of attacks. Particularly, the systems based on iris are vulnerable to direct attacks consisting on the presentation of a fake iris to the sensor trying to access the system as it was from a legitimate user. The analysis of some countermeasures against this type of attacking scheme is the problem addressed in the present paper. Several state-of-the-art methods were implemented and included in a feature selection framework so as to determine the best cardinality and the best subset that conducts to the highest classification rate. Three different classifiers were used: Discriminant analysis, K nearest neighbours and Support Vector Machines. The implemented methods were tested in existing databases for iris liveness purposes (Biosec and Clarkson) and in a new fake database which was constructed for evaluation of iris liveness detection methods in the mobile scenario. The results suggest that this new database is more challenging than t
he others. Therefore, improvements are required in this line of research to achieve good performance in real world mobile applications.
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