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
Adaptive simplification of solution for support vector machine
Pattern Recognition
Optimal Features Subset Selection Using Genetic Algorithms for Iris Recognition
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
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 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
Iris Recognition in Nonideal Situations
ISC '09 Proceedings of the 12th International Conference on Information Security
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In this paper, we present algorithms for iris segmentation, feature extraction and selection, and iris pattern matching. To segment the nonideal iris images accurately, we propose level set based curve evolution approaches using the edge-stopping function and the energy minimization algorithm. Daubechies Wavelet Transform (DBWT) is used to extract the textural features, and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithm is deployed to reduce the feature dimension without compromising the accuracy. To speed up the matching process and to control the misclassification error, we apply a combined approach called Adaptive Asymmetrical SVMs (AASVMs). The verification performance of the proposed scheme is validated using the UBIRIS Version 2, the ICE 2005, and the WVU datasets.