Conference paper
Model-based region growing segmentation of textured images
International Conference on Acoustics, Speech, and Signal Processing, pp.2313-2316
IEEE
International Conference on Acoustics, Speech, and Signal Processing, ICASSP-90 (Albuquerque, NM. USA, 23/04/1990–26/04/1990)
1990
Abstract
An approach to the use of a region-growing technique for segmentation of textured images is presented. The algorithm is model-based, with each mixture region in the image modeled by a noncausal Gaussian Markov random field (GMRF). No a priori knowledge about the different texture regions, their associated texture parameters, or the available number of texture regions is required. The algorithm first partitions the image into small disjointed square windows. The texture within each window is modeled by a noncausal GMRF. Most of the windows are homogeneous. A hierarchical merge-split region-growing process is then employed to reconstruct most of the homogeneous regions that are presented in the image. The growth of various homogeneous regions is directed by a texture distance defined by a likelihood ratio test statistic based on the underlying GMRF model assumptions. The algorithm was tested on real textured images and proved to be robust and effective
Details
- Title
- Model-based region growing segmentation of textured images
- Authors/Creators
- P.W. Fung (Author/Creator) - The University of Western AustraliaG. Grebbin (Author/Creator) - The University of Western AustraliaY. Attikiouzel (Author/Creator) - The University of Western Australia
- Publication Details
- International Conference on Acoustics, Speech, and Signal Processing, pp.2313-2316
- Conference
- International Conference on Acoustics, Speech, and Signal Processing, ICASSP-90 (Albuquerque, NM. USA, 23/04/1990–26/04/1990)
- Publisher
- IEEE
- Identifiers
- 991005544892207891
- Copyright
- © 1990 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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