Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pupil and Iris Localization for Iris Recognition in Mobile Phones
SNPD-SAWN '06 Proceedings of the Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
A robust eyelash detection based on iris focus assessment
Pattern Recognition Letters
Journal of Cognitive Neuroscience
Cascade adaboost classifiers with stage optimization for face detection
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A study on iris image restoration
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
A new feature extraction method using the ICA filters for iris recognition system
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
IEEE Transactions on Circuits and Systems for Video Technology
Attack against robust watermarking-based multimodal biometric recognition systems
BioID'11 Proceedings of the COST 2101 European conference on Biometrics and ID management
Robust watermarking in iris recognition: application scenarios and impact on recognition performance
ACM SIGAPP Applied Computing Review
Watermarking as a means to enhance biometric systems: a critical survey
IH'11 Proceedings of the 13th international conference on Information hiding
Two-factor biometric recognition with integrated tamper-protection watermarking
CMS'11 Proceedings of the 12th IFIP TC 6/TC 11 international conference on Communications and multimedia security
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In this paper, we propose a new iris feature watermarking method on face data. This research has following three objectives. First, by using watermarked iris features in addition to face data, the multimodal biometric authentication can be possible, which can increase the authentication accuracy. Second, in case that the saved face data is illegally let out and privacy infringement happens, by checking the inserted iris feature watermark, we can solve the legal responsibility problem about the outflow of face data. In detail, if the iris feature watermark cannot be extracted from the outflow face data, we can insist that the face data is let out from other organization instead of ours. Third, in case that "the iris features need to be transmitted via non-secure and noisy communication channel" [1], it can be invisibly hidden on face data by our method. For the first objective, the face recognition accuracy with iris feature watermark should not be degraded. For the second and third objectives, the inserted iris watermark should be "strong" enough to be extracted irrespective of various kinds of attacks (such as blurring, cropping and rotation attacks) and noise insertion on face data. This research has three advantages compared to previous works. First, to overcome the vulnerability of blurring attack to previous biometric watermarking based on spatial domain, we use the watermarking method in frequency domain. Second, to reduce the degradation of face recognition accuracy due to iris watermarking, we insert the watermark into mid and high frequency bands. Third, through using individual unique iris features for biometric watermarking information and secondary authentication, the security level is much enhanced and we can solve legal responsibility problem about the outflow of face data. Experimental results showed that our algorithm could be used to accomplish above objectives.