Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Crystal growth and dendritic solidification
Journal of Computational Physics
Shape Modeling with Front Propagation: A Level Set Approach
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
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition Using Collarette Boundary Localization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
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
An improved handwritten Chinese character recognition system using support vector machine
Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
Experiments with an Improved Iris Segmentation Algorithm
AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
Adaptive simplification of solution for support vector machine
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
An Effective Approach for Iris Recognition Using Phase-Based Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris segmentation using geodesic active contours
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Coarse iris classification using box-counting to estimate fractal dimensions
Pattern Recognition
Selection of optimal features for iris recognition
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Iris recognition with support vector machines
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On Techniques for Angle Compensation in Nonideal Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Iris recognition based on zigzag collarette region and asymmetrical support vector machines
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
A review of information fusion techniques employed in iris recognition systems
International Journal of Advanced Intelligence Paradigms
Effective elliptic fitting for iris normalization
Computer Vision and Image Understanding
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We present algorithms for iris segmentation, feature extraction and selection, and iris pattern matching. To segment the inner boundary from a nonideal iris image, we apply a level set based curve evolution approach using the edge stopping function, and to detect the outer boundary, we employ the curve evolution approach using the regularized Mumford-Shah segmentation model with an energy minimization algorithm. Daubechies wavelet transform (DBWT) is used to extract the textural features, and genetic algorithms (GAs) are deployed to select the subset of informative features by combining the valuable outcomes from the multiple feature selection criteria without compromising the recognition accuracy. To speed up the matching process and to control the misclassification error, we apply a combined approach called the adaptive asymmetrical support vector machines (AASVMs). The parameter values of SVMs are also optimized in order to improve the overall generalization performance. The verification and identification performance of the proposed scheme is validated using the UBIRIS Version 2, the ICE 2005, and the WVU datasets.