Resumen de Implementation of an artificial neural network for the segmentation of texture images
Antonio Mosquera González, Diego Cabello Ferrer, M. J. Carreira Nouche, Manuel Francisco González Penedo
In this work we describe the implementation of an artificial neural network, an extension of Hopfield's model, for the segmentation of textured images. We use a Markov random field in order to model the textures in the image. The problem is approached in terms of the minimization of a cost function that is projected onto the network. It provides a locally optimal solution to the problem of the classification of M* M pixels into K classes (textures). The experimental results obtained on artificial and natural images show the validity of the architecture we propose
