Mathematics – Statistics Theory
Scientific paper
2002-06-18
Mathematics
Statistics Theory
13 pages, 10 figures
Scientific paper
The network flow optimization approach is offered for Bayesian segmentation of gray-scale and color images. It is supposed image pixels are characterized by a feature function taking finite number of arbitrary rational values (it can be either intensity values or other characteristics of images). The clusters of homogeneous pixels are described by labels with values in another set of rational numbers. They are assumed to be dependent and distributed according to either the exponential or the Gaussian Gibbs law. Instead traditionally used local neighborhoods of nearest pixels the completely connected graph of dependence of all pixels is employed for the Gibbs prior distributions. The methods developed reduce the problem of segmentation to the problem of determination of the minimum network cuts.
No associations
LandOfFree
Fast algorithms of Bayesian Segmentation of Images does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Fast algorithms of Bayesian Segmentation of Images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fast algorithms of Bayesian Segmentation of Images will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-366923