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	A unified model of GMRF and MOG for image segmentation
	Yu, Peng ; Tong, Xing-Wei ; Feng, Ju-Fu
	2005
英文摘要	In texture segmentation, features must be firstly extracted In the mlxture-of-Gausslan (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. ? 2005 IEEE.; EI; 0
语种	英语
出处	EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/315548]
专题	数学科学学院 信息科学技术学院
推荐引用方式 GB/T 7714	Yu, Peng,Tong, Xing-Wei,Feng, Ju-Fu. A unified model of GMRF and MOG for image segmentation. 2005-01-01.

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