Refereed full papers (journals, book chapters, international conferences)

2004

@article{DeC2004,
	vgclass =	{refpap},
	author =	{Huawu Deng	and David A. Clausi},
	title =	{Unsupervised image segmentation using a simple {MRF} model
	with a new implementation scheme},
	journal =	{Pattern Recognition},
	volume =	{37},
	number =	{12},
	pages =	{2323--2335},
	month =	{December},
	year =	{2004},
	url =	{http://dx.doi.org/10.1016/j.patcog.2004.04.015},
	abstract =	{A simple Markov random field model with a new
	implementation scheme is proposed for unsupervised previous termimage
	segmentation based on image features. The traditional two-component MRF
	model for segmentation requires training data to estimate necessary
	model parameters and is thus unsuitable for unsupervised segmentation.
	The new implementation scheme solves this problem by introducing a
	function-based weighting parameter between the two components. Using
	this method, the simple MRF model is able to automatically estimate
	model parameters and produce accurate unsupervised segmentation
	results. Experiments demonstrate that the proposed algorithm is able to
	segment various types of images (gray scale, color, texture) and
	achieves an improvement over the traditional method.},
}