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Face Recognition Using Localized Kernel Eigen Spaces
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In this paper, we are proposed that the Feature selection technique and Information fusion procedure for obtaining the accuracy in visual and thermal images. Phase congruency feature maps are extracted from the images and they are further implemented and developed by the approach of novel modular kernel Eigen spaces. Smaller sub-regions are merged to form large set of features which are then projected into higher dimensional spaces. This technique helps us to overcome the expression variations and variations due to temperature. Compared to the other conventional methods, the Feature selection technique proves to be better than any other face recognition techniques for finding the accuracy of an image.
Keywords
Kernel Methods (KES), Phase Congruency, Multisensor.
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