Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ordinal Measures for Iris Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensor interoperability and fusion in signature verification: a case study using tablet PC
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
IEEE Transactions on Circuits and Systems for Video Technology
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As a reliable personal identification method, iris recognition has been widely used for a large number of applications. Since a variety of iris devices produced by different vendors may be used for some large-scale applications, it is necessary to match heterogeneous iris images against the variations of sensors, illuminators, imaging distance and imaging conditions. This paper aims to improve cross-sensor iris recognition performance using a novel multi-biometrics strategy. The novelty of our solution is that both iris and periocular biometrics in heterogeneous iris images are combined through score-level information fusion for approaching the problem of iris sensor interoperability. Then the improved feature extraction method, namely Multi-Directions Ordinal Measures, is applied to encode both iris and periocular images to describe the distinctive features. The experimental results on images captured from three iris devices, including two close-range iris devices and one long-range iris device, demonstrate the effectiveness of the proposed method.