A Novel Method For Generation Of Random Fields For Boundary Detection And Classification Of Images
C.H. Nagaraju, Srinivasa Rao · 2008
Markov random field(MRF) theory has been widely applied to the challenging problem of Image Segmentation. Image segmentation is a task that classifies pixels of an Image using different labels so that the Image is partitioned into non-overlapping labeled regions. Image segmentation is one of the most difficult problems that researchers are facing because most of the real objects have complex shapes, boundaries and morphology, and true images are often corrupted by noise that cannot be ignored. To tackle the difficult problem of image segmentation, researchers have proposed a variety of methods. In this paper, a new texture segmentation method using compound MRFs is proposed, in which the label MRF and boundary MRF are coupled with gray level watershed method to help improve the segmentation performance. The boundary model is relatively general and does not need prior training on