A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine vision
The nature of statistical learning theory
The nature of statistical learning theory
Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
Digital Image Processing
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Techniques for an Iris Recognition System with High Performance
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Iris recognition based on score level fusion by using SVM
Pattern Recognition Letters
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
A study on fast iris restoration based on focus checking
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Fake iris detection by using purkinje image
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A real-time focusing algorithm for iris recognition camera
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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With the increasing needs for higher security level, biometric systems have been widely used for many applications. Among biometrics, iris recognition system has been in the limelight for high security applications. Until now, most researches have been focused on iris identification algorithm and iris camera system. However, after the recent report of attacking iris recognition system by fake iris such as printed, photography and contact lens iris has been disclosed, the importance of fake iris detection is much increased. So, we propose the new method of detecting fake iris. This research has following three advances compared to previous works. First, to detect fake iris, we check both the size change of pupil and the change of iris features in local iris area (near pupil boundary) by visible light. Second, to detect the change of local iris features, we used multiple wavelet filters having Gabor and Daubechies bases. Third, to enhance the detecting accuracy of fake iris, we used a hierarchical SVM (Support Vector Machine) based on extracted wavelet features.