Modification of correlation kernels in SVM, KPCA and KCCA in texture classification
Yo Horikawa · Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. · 2006
Modified versions of the correlation kernels in the kernel methods, e.g., SVMs, kPCA and kCCA are presented, which are based on the L/sub p/ norm and max norm as well as the blindness of the odd-order autocorrelations to sinusoidal or symmetrically distributed signals. The poor generalization of the higher-order correlation kernels and the inferior performance of the correlation kernels of odd-orders to even-orders are improved with the modifications. The performance of the modified correlation kernels is evaluated and compared in texture classification experiments.