Title

Preserving Objects in Markov Random Fields Region Growing Image Segmentation

Document Type

Article

Publication Date

5-1-2012

Department

Computing

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