¹ School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
² School of Information and Software Engineering, University of Electronic Science and Technology of China. Chengdu, Sichuan, 610054, P.R China.

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Abstract—A new Student’s t-distribution finite mixture model is proposed which incorporates the local spatial information of the pixels. The pixels’ label probability proportions are explicitly modelled as probability vectors in the proposed model. We use the gradient descend method to estimate the parameters of the proposed model. Comprehensive experiments are performed for synthetic and natural grayscale images. The experimental results demonstrate that the superiority of the proposed model over some other models.

Index Terms—Spatially variant finite mixture model, Student’s t-distribution, Image segmentation, Gradient descent

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Cite: Taisong Xiong, Jianping Gou, and Yunbo Rao, " An Extension of the Student's T-distribution Mixture Model and the Gradient Descent Method," Journal of Computers vol. 8, no. 7, pp. 1750-1757, 2013.