Stochastic modeling approach to region-based image segmentation

Aly A. Farag; Edward J. Delp

doi:10.1117/12.57118

1 February 1992 Stochastic modeling approach to region-based image segmentation

Aly A. Farag, Edward J. Delp

Proceedings Volume 1609, Model-Based Vision Development and Tools; (1992) https://doi.org/10.1117/12.57118
Event: Robotics '91, 1991, Boston, MA, United States

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.

Citation Download Citation

Aly A. Farag and Edward J. Delp "Stochastic modeling approach to region-based image segmentation", Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); https://doi.org/10.1117/12.57118

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