Texture-based segmentation using Markov random field models

Chi-hsin Wu; Peter C. Doerschuk

doi:10.1117/12.179216

30 June 1994 Texture-based segmentation using Markov random field models

Chi-hsin Wu, Peter C. Doerschuk

Proceedings Volume 2304, Neural and Stochastic Methods in Image and Signal Processing III; (1994) https://doi.org/10.1117/12.179216
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

We describe segmentation based on textures using the label and image model of D. Geman et al. We replace their maximum a posteriori estimation criteria with a Bayesian estimator that minimizes the sum of the pixel misclassification probabilities. The new estimation goal allows the use of a different computational algorithm based on approximating lattices by trees. An example demonstrating an accurate segmentation of a collage of Brodatz textures is included.

Citation Download Citation

Chi-hsin Wu and Peter C. Doerschuk "Texture-based segmentation using Markov random field models", Proc. SPIE 2304, Neural and Stochastic Methods in Image and Signal Processing III, (30 June 1994); https://doi.org/10.1117/12.179216

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