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	BYY harmony learning of t-mixtures with the application to image segmentation based on contourlet texture features
	Jiang, Yunsheng ; Liu, Chenglin ; Ma, Jinwen
	2016
关键词	Bayesian Ying-Yang (BYY) harmony learning Multivariate t-mixture Gradient learning Model selection Contourlet texture features AUTOMATED MODEL SELECTION GAUSSIAN MIXTURE FINITE MIXTURE ALGORITHM DISTRIBUTIONS RPCL
英文摘要	In this paper, we extend Bayesian Ying-Yang (BYY) harmony learning to the case of multivariate t-mixtures and propose a gradient BYY harmony learning algorithm that can automatically determine the number of actual t-distributions in a dataset during parameter learning. It is demonstrated by simulation experiments that this proposed algorithm for t-mixtures is both effective and stable on model selection and parameter estimation. Moreover, by mainly utilizing certain contourlet texture features from an image, the proposed algorithm is successfully applied to unsupervised image segmentation, showing considerable advantages for both general and multi-texture images. (C) 2015 Elsevier B.V. All rights reserved.; SCI(E); EI; ARTICLE; jwma@math.pku.edu.cn; ,SI; 262-274; 188
语种	英语
出处	EI ; SCI
出版者	NEUROCOMPUTING
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/437281]
专题	数学科学学院
推荐引用方式 GB/T 7714	Jiang, Yunsheng,Liu, Chenglin,Ma, Jinwen. BYY harmony learning of t-mixtures with the application to image segmentation based on contourlet texture features. 2016-01-01.

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