期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2012
卷号：4
期号：4
页码：151
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Face verification is an important problem. The problem of designing and evaluating discriminativeapproaches without explicit age modelling is used. To find the gradient orientation discard magnitudeinformation. Using hierarchical information this representation can be further improved which results inthe use of gradient orientation pyramid. When combined with a structural risk minimization support vectormachine with genetic algorithm, gradient orientation pyramid demonstrate excellent performance.Gradient Orientation of each color channel of human faces is robust under age progression. The featurevector which is computed as the cosines of the difference between gradient orientations at all pixels, isgiven as the input to the structural risk minimization support vector machine classifier. The classifier isused to divide the feature space into two classes, one for the intrapersonal pairs and the other forextrapersonal pairs. Genetic algorithm plays an important role in improving the performance of the system.The system outperformed other classifiers such as support vector machine and boosting support vectormachine.
