Image segmentation using Gibbs-Markov random fields based on bond percolation

Iftekhar Hussain; Todd Randall Reed

doi:10.1117/12.217418

22 August 1995 Image segmentation using Gibbs-Markov random fields based on bond percolation

Iftekhar Hussain, Todd Randall Reed

Proceedings Volume 2564, Applications of Digital Image Processing XVIII; (1995) https://doi.org/10.1117/12.217418
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

This paper presents a new bond percolation base model to determine the clique potential parameters of a Gibbs-Markov model used in image segmentation. Previously, experimentally determined fixed values were used for these parameters which did not depend on the underlying image data. Using the proposed model, the clique potential parameters are now derived as a function of local characteristics of the image under consideration. The suitability of this approach to multiscale processing via application of the renormalization group transformation is also discussed.

Citation Download Citation

Iftekhar Hussain and Todd Randall Reed "Image segmentation using Gibbs-Markov random fields based on bond percolation", Proc. SPIE 2564, Applications of Digital Image Processing XVIII, (22 August 1995); https://doi.org/10.1117/12.217418

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