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
Recommended Citation
Hernandez, G., & Dasgupta, D. (1998). Texture segmentation with a Cascade Correlation Neural Network using Markov Random Fields. Intelligent Engineering Systems Through Artificial Neural Networks, 1998, 467-472. Retrieved from https://digitalcommons.memphis.edu/facpubs/3238
