Adaptive a symmetrical SVM and Genetic Algorithms based iris recognition

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2008, Pages

  Roy, Kaushik ^a   Bhattacharya, Prabir ^a  

^a Concordia University ^*  (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE ALGORITHMS; BIOMETRICS; ECONOMIC AND SOCIAL EFFECTS; GENETIC ALGORITHMS; SUPPORT VECTOR MACHINES;

FEATURE SUBSET SELECTION; FEATURE VECTORS; IRIS RECOGNITION; MISCLASSIFICATION ERROR; MISCLASSIFICATIONS; MULTIPLE FEATURES; PERFORMANCE ISSUES; SUPPORT VECTOR;

FEATURE EXTRACTION;

EID: 77957935760     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761675     Document Type: Conference Paper

References (7)

1. J. Daugman, "Demodulation by complex-valued wavelets for stochastic pattern recognition," Internat. J. Wavelets, Multi-Res. and Info. Processing, vol. 1, pp. 1-17, 2003.
2. V. N. Vapnik, Statistical Learning Theory, J. Wiley, New York, 1998.
3. Iris Challenge Evaluation (ICE) dataset found at http://iris.nist.gov/ ICE/.
4. Iris Dataset obtained from West Virginia University (WVU). http://www.wvu.edu/.
5. F. Tan, X. Fu, Y. Zhang, A. G. Bourgeois, "Improving feature subset selection using a genetic algorithm for microarray gene expression data," IEEE Congress on Evolutionary Computation, pp. 2529-2534, 2006.
6. K. Roy and P. Bhattacharya, "Iris recognition based on collarette region and asymmetrical support vector machines," Internat. Conf. Image Anal. and Recog. (ICIAR), Montreal, Canada, 2007. Springer Lecture Note Series in Computer Science (LNCS), vol. 4633, pp. 854-865.
7. Adaptive simplification of solution for support vector machine