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Proceedings Paper

An image threshold selection method based on the Burr distribution
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Paper Abstract

It is important to accurately fit the unknown probability density functions of background or object. To solve this problem, the Burr distribution is introduced. Three-parameter Burr distribution can cover a wide range of distribution. The expectation maximization algorithm is used to deal with the estimation difficulty in the Burr distribution model. The expectation maximization algorithm starts from a set of selected appropriate parameters’ initial values, and then iterates the expectation-step and maximization-step until convergence to produce result parameters. The experiment results show that the Burr distribution could depicts quite successfully the probability density function of a significant class of image, and comparatively the method has low computing complexity.

Paper Details

Date Published: 30 November 2012
PDF: 7 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85582K (30 November 2012); doi: 10.1117/12.2001143
Show Author Affiliations
Xiaohong Xie, Minjiang Univ. (China)
Rongteng Wu, Minjiang Univ. (China)


Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)

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