Fusion of Edge Information in Markov Random Fields Region Growing Image Segmentation
Computing Sciences and Computer Engineering
This paper proposes an algorithm that fuses edge information into Markov Random Fields (MRF) region growing based image segmentation. The idea is to segment the image in a way that takes edge information into consideration. This is achieved by modifying the energy function minimization process so that it would penalize merging regions that have real edges in the boundary between them. Experimental results confirming the hypothesis that the addition of edge information increases the precision of the segmentation by ensuring the conservation of the objects contours during the region growing.
Image Analysis and Recognition
(2010). Fusion of Edge Information in Markov Random Fields Region Growing Image Segmentation. Image Analysis and Recognition, 96-104.
Available at: https://aquila.usm.edu/fac_pubs/21522