Useful features for human verification in near-infrared periocular images
Image and Vision Computing
A fusion approach to unconstrained iris recognition
Pattern Recognition Letters
A comprehensive approach for skin recognition
International Journal of Biometrics
Soft biometric classification using local appearance periocular region features
Pattern Recognition
Genetically identical irises have texture similarity that is not detected by iris biometrics
Computer Vision and Image Understanding
Multispectral scleral patterns for ocular biometric recognition
Pattern Recognition Letters
Periocular recognition using retinotopic sampling and gabor decomposition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Robust periocular recognition by fusing local to holistic sparse representations
Proceedings of the 6th International Conference on Security of Information and Networks
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Human recognition based on the iris biometric is severely impacted when encountering non-ideal images of the eye characterized by occluded irises, motion and spatial blur, poor contrast, and illumination artifacts. This paper discusses the use of the periocular region surrounding the iris, along with the iris texture patterns, in order to improve the overall recognition performance in such images. Periocular texture is extracted from a small, fixed region of the skin surrounding the eye. Experiments on the images extracted from the Near Infra-Red (NIR) face videos of the Multi Biometric Grand Challenge (MBGC) dataset demonstrate that valuable information is contained in the periocular region and it can be fused with the iris texture to improve the overall identification accuracy in non-ideal situations.