Noisy iris image matching by using multiple cues

Authors:
Tieniu Tan;Xiaobo Zhang;Zhenan Sun;Hui Zhang
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, PR China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, PR China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, PR China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, PR China
Venue:
Pattern Recognition Letters
Year:
2012

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Abstract

Noisy iris recognition under visible lighting has recently drawn much attention. This paper proposes an effective method for visible light iris image matching by using multiple characteristics of iris and eye images. The method consists of image preprocessing, iris data matching, eye data matching, and multi-modal fusion. Ordinal measures and color analysis are adopted for iris data matching, and texton representation and semantic information are used for eye data matching. After we obtain the four matching scores, a robust score level fusion strategy is applied to generate the dissimilarity measure of the two images under consideration. Extensive experiments on the UBIRIS.v2 database and the NICE.II training dataset demonstrate that the proposed method is effective. Our method significantly outperforms all other algorithms submitted to the Noisy Iris Challenge Evaluation-Part II (NICE.II), an open contest in noisy iris image matching.