Preserving Objects in Markov Random Fields Region Growing Image Segmentation
Document Type
Article
Publication Date
5-1-2012
School
Computing Sciences and Computer Engineering
Abstract
This paper proposes an algorithm that preserves objects in Markov Random Fields (MRF) region growing based image segmentation. This is achieved by modifying the MRF energy minimization process so that it would penalize merging regions that have real edges in the boundary between them. Experimental results show that the integration of edge information increases the precision of the segmentation by ensuring the conservation of the objects contours during the region-growing process.
Publication Title
Pattern Analysis and Applications
Volume
15
Issue
2
First Page
155
Last Page
161
Recommended Citation
Dawoud, A.,
Netchaev, A.
(2012). Preserving Objects in Markov Random Fields Region Growing Image Segmentation. Pattern Analysis and Applications, 15(2), 155-161.
Available at: https://aquila.usm.edu/fac_pubs/192