A new algorithm for training multi-layered morphological networks

Abstract

In this work we present an algorithm for training an associative memory based on the so-called multi-layered morphological perceptron with maximal support neighborhoods. We compare the proposal with the original one by performing some experiments with real images. We show the superiority of the new one. We also give formal conditions for correct classification. We show that the proposal can be applied to the case of gray-level images and not only binary images. © Springer-Verlag Berlin Heidelberg 2007.