Share Email Print

Proceedings Paper

An image threshold selection method based on the Burr distribution
Format Member Price Non-Member Price
PDF $17.00 $21.00

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)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?