Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
A Stereo Matching Paradigm Based on the Walsh Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Programming
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experimental Evaluation of Iris Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Toward Noncooperative Iris Recognition: A Classification Approach Using Multiple Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
A robust segmentation approach to iris recognition based on video
AIPR '08 Proceedings of the 2008 37th IEEE Applied Imagery Pattern Recognition Workshop
Exploiting Walsh-based attributes to stereo vision
IEEE Transactions on Signal Processing
A similarity measure for stereo feature matching
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
A computational efficient Iris extraction approach in unconstrained environments
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Robust iris indexing scheme using geometric hashing of SIFT keypoints
Journal of Network and Computer Applications
Fast and iterative algorithm for iris detection with orthogonal polynomials transform
Proceedings of the 2011 International Conference on Communication, Computing & Security
Multi-stage visible wavelength and near infrared iris segmentation framework
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Iris localization in frontal eye images for less constrained iris recognition systems
Digital Signal Processing
Efficient iris segmentation method in unconstrained environments
Pattern Recognition
Computer Methods and Programs in Biomedicine
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Biometric research has experienced significant advances in recent years given the need for more stringent security requirements. More important is the need to overcome the rigid constraints necessitated by the practical implementation of sensible but effective security methods such as iris recognition. An inventive iris acquisition method with less constrained image taking conditions can impose minimal to no constraints on the iris verification and identification process as well as on the subject. Consequently, to provide acceptable measures of accuracy, it is critical for such an iris recognition system to be complemented by a robust iris segmentation approach to overcome various noise effects introduced through image capture under different recording environments and scenarios. This research introduces a robust and fast segmentation approach towards less constrained iris recognition using noisy images contained in the UBIRIS.v2 database (the second version of the UBIRIS noisy iris database). The proposed algorithm consists of five steps, which include: (1) detecting the approximate localization of the eye area of the noisy image captured at the visible wavelength using the extracted sclera area, (2) defining the outer iris boundary which is the boundary between iris and sclera, (3) detecting the upper and lower eyelids, (4) conducting the verification and correction for outer iris boundary detection and (5) detecting the pupil area and eyelashes and providing means for verification of the reliability of the segmentation results. The results demonstrate that the accuracy is estimated as 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at =97% in a ''Noisy Iris Challenge Evaluation (NICE.I)'' in an international competition that involved 97 participants worldwide, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time.