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	A unified model of GMRF and MOG for image segmentation
	Yu, P ; Tong, XW ; Feng, JF
	2005
关键词	mixture-of-Gaussian Gauss Markov random field image sigmentation textured image EM algorithm
英文摘要	In texture segmentation, features must be firstly extracted in the mixture-of-Gaussian (MOG) models. In this paper, we combine MOG model with Gauss Markov random field (GMRF) model and get a unification model. This unified model takes interaction coefficients of neighbor pixels as parameters. We derivate a set of parameters estimation equations by Expectation-Maximization (EM) algorithms and apply them to a two-class texture segmentation problem. Experimental results show the efficiencies and strengths of the model.; Computer Science, Artificial Intelligence; Imaging Science & Photographic Technology; CPCI-S(ISTP); 0
语种	英语
出处	SCI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/315429]
专题	数学科学学院
推荐引用方式 GB/T 7714	Yu, P,Tong, XW,Feng, JF. A unified model of GMRF and MOG for image segmentation. 2005-01-01.

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