Preserving objects in Markov Random Fields region growing image segmentation

• DOI: 10.1007/s10044-011-0198-x
• Publication Date: 2011-03-01T21:02:52Z
• Authors: Amer Dawoud; Anton Netchaev
• Keywords: energy function minimization; fusion; Computer Sciences; segmentation; Physical Sciences and Mathematics; 0211 other engineering and technologies; markov random fields; 02 engineering and technology

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.