Fusion of visual cues of intensity and texture in Markov random fields image segmentation
Fusion of visual cues of intensity and texture in Markov random fields image segmentation
- Author(s): A. Dawoud and A. Netchaev
- DOI: 10.1049/iet-cvi.2011.0233
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- Author(s): A. Dawoud 1 and A. Netchaev 1
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View affiliations
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Affiliations:
1: School of Computing, University of Southern Mississippi, Hattiesburg, USA
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Affiliations:
1: School of Computing, University of Southern Mississippi, Hattiesburg, USA
- Source:
Volume 6, Issue 6,
November 2012,
p.
603 – 609
DOI: 10.1049/iet-cvi.2011.0233 , Print ISSN 1751-9632, Online ISSN 1751-9640
This study proposes an algorithm that fuses visual cues of intensity and texture in Markov random fields region growing texture image segmentation. The idea is to segment the image in a way that takes EdgeFlow edges into consideration, which provides a single framework for identifying objects boundaries based on texture and intensity descriptors. This is achieved by modifying the energy minimisation process, so that it would penalise merging regions that have EdgeFlow edges in the boundary between them. Experimental results confirm the hypothesis that the integration of edge information increases the precision of the segmentation by ensuring the conservation of the homogeneous objects contours during the region growing process.
Inspec keywords: image segmentation; minimisation; image texture; Markov processes; random processes
Other keywords:
Subjects: Optimisation techniques; Optical, image and video signal processing; Optimisation techniques; Markov processes; Markov processes; Computer vision and image processing techniques
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