Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Efficient Non-Maximum Suppression
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Enhancement and Registration Schemes for Matching Conjunctival Vasculature
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Iris Recognition: The Path Forward
Computer
Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Fusion of Periocular and Iris Biometrics in Non-ideal Imagery
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
On the use of multispectral conjunctival vasculature as a soft biometric
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Handbook of Multibiometrics
Periocular Biometrics in the Visible Spectrum
IEEE Transactions on Information Forensics and Security
On Techniques for Angle Compensation in Nonideal Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
A comprehensive approach for sclera image quality measure
International Journal of Biometrics
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Biometrics is the science of recognizing people based on their physical or behavioral traits such as face, fingerprints, iris, and voice. Among these characteristics, ocular biometrics has gained popularity due to the significant progress made in iris recognition. However, iris recognition is unfavorably influenced by the non-frontal gaze direction of the eye with respect to the acquisition device. In such scenarios, additional parts of the eye, such as the sclera (the white of the eye) may be of significance. In this article, we investigate the use of the sclera texture and vasculature patterns evident in the sclera as a potential biometric. Iris patterns are better discerned in the near infrared spectrum (NIR) while vasculature patterns are better discerned in the visible spectrum (RGB). Therefore, multispectral images of the eye, consisting of both NIR and RGB channels, are used in this work in order to ensure that both the iris and the vasculature patterns are imaged. The contributions of this work include: (a) the assembling of a multispectral eye database to initiate research on this topic; (b) the design of a novel algorithm for sclera segmentation based on a normalized sclera index measure; and (c) the evaluation of three different feature extraction and matching schemes on the assembled database in order to examine the potential of utilizing the sclera and the accompanying vasculature pattern as biometric cues. Experimental results convey the potential of this biometric in an ocular-based recognition system.