Texture classification with kernel principal component analysis

Kernel principal component analysis (PCA) is presented as a mechanism for extracting textural information. Using the polynomial kernel, higher order correlations of input pixels can be easily used as features for classification. As a result, supervised texture classification can be performed using a neural network