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Proceedings Paper

Image segmentation using Gibbs-Markov random fields based on bond percolation
Author(s): Iftekhar Hussain; Todd Randall Reed
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Paper 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.

Paper Details

Date Published: 22 August 1995
PDF: 11 pages
Proc. SPIE 2564, Applications of Digital Image Processing XVIII, (22 August 1995); doi: 10.1117/12.217418
Show Author Affiliations
Iftekhar Hussain, Univ. of California/Davis (United States)
Todd Randall Reed, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 2564:
Applications of Digital Image Processing XVIII
Andrew G. Tescher, Editor(s)

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