On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Another look at the dominant point detection of digital curves
Pattern Recognition Letters
Direct Least Square Fitting of Ellipses
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
Robust Real-Time Face Detection
International Journal of Computer Vision
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Experiments with an Improved Iris Segmentation Algorithm
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
ENCARA2: Real-time detection of multiple faces at different resolutions in video streams
Journal of Visual Communication and Image Representation
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Overview of the Multiple Biometrics Grand Challenge
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
An Automated Video-Based System for Iris Recognition
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move
Proceedings of the 2010 Symposium on Information and Communication Technology
Effective elliptic fitting for iris normalization
Computer Vision and Image Understanding
Feature-domain super-resolution for iris recognition
Computer Vision and Image Understanding
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Video-based Automated System for Iris Recognition (VASIR) performs two-eye detection, best quality image selection by adapting human vision and edge density methods, and iris verification for identifying a person. A new method of iris segmentation is implemented and evaluated that uses a combination of contour processing and Hough transform algorithms along with a new approach to eyelid detection. User-interaction is reduced by using automatic threshold selection to detect the pupil and by defining it to be a minimum boundary radius of the iris. VASIR's performance is evaluated with the MBGC datasets which were captured under unconstrained environments. The results show that the new method significantly improves the segmentation of the iris region and consequently the matching results. Our method also demonstrates that automated best image selection is nearly equivalent to human selection.