Title

Texture segmentation with a Cascade Correlation Neural Network using Markov Random Fields

Abstract

In this paper a Cascade Correlation Neural Network is used to segment an image according to some known textures. The texture labeling process is modeled using a Markov Random Field (MRF); this model allows to classify a pixel in a determined texture using information from its neighbors. The neural network learns the characteristics of the MRF that model the texture labeling piocess for a set of known textures.

Publication Title

Intelligent Engineering Systems Through Artificial Neural Networks

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