A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining multiple matchers for a high security fingerprint verification system
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Fusion in Biometrics
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Combining face and iris biometrics for identity verification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Robust Multi-modal and Multi-unit Feature Level Fusion of Face and Iris Biometrics
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Multibiometric cryptosystem: model structure and performance analysis
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Fusion of near infrared face and Iris biometrics
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Machine Vision and Applications
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In this paper, we present the biometric authentication system based on the fusion of two user-friendly biometric modalities: Iris and Face. Using one biometric feature can lead to good results, but there is no reliable way to verify the classification. In order to reach robust identification and verification we are combining two different biometric features. we specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from iris and face. And then to obtain Reduced Joint Feature Vector(RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.