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Proceedings Paper

Stochastic modeling approach to region-based image segmentation
Author(s): Aly A. Farag; Edward J. Delp
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Paper Abstract

The problem of region-based segmentation is examined and a new algorithm for MAP segmentation is introduced. The observed image is modeled as a composite of two processes: a high-level process that describes the various regions in the images and a low-level process that describes each particular region. A Gibbs-Markov random field model is used to describe the high-level process and a simultaneous autoregressive random field model is used to describe the low-level process. The MAP segmentation algorithms is formulated from the two models and a recursive implementation for the algorithm is presented. Results of the algorithm on various synthetic and natural textures clearly indicate the effectiveness of the approach to texture segmentation.

Paper Details

Date Published: 1 February 1992
PDF: 24 pages
Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); doi: 10.1117/12.57118
Show Author Affiliations
Aly A. Farag, Univ. of Louisville (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 1609:
Model-Based Vision Development and Tools
Rodney M. Larson; Hatem N. Nasr, Editor(s)

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