Translator Disclaimer
30 November 2012 An image threshold selection method based on the Burr distribution
Author Affiliations +
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaohong Xie and Rongteng Wu "An image threshold selection method based on the Burr distribution", Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85582K (30 November 2012);


A threshold selection method based on edge preserving
Proceedings of SPIE (December 13 2015)
A variable parameter parametric snake method
Proceedings of SPIE (December 07 2015)
Multicolor well-composed pictures
Proceedings of SPIE (January 03 1995)
Digital topology of multicolor images
Proceedings of SPIE (October 09 1994)

Back to Top