Optimal Parameter Algorithm for Image Segmentation

Author

Tian, WenJie ; Geng, Yu ; Liu, JiCheng ; Ai, Lan

Author_Institution

Autom. Inst., Beijing Union Univ., Beijing, China

fYear

2009

fDate

13-14 Dec. 2009

Firstpage

179

Lastpage

182

Abstract

An improved artificial fish swarm algorithm is proposed to search the optimal parameter combination in this paper. It is concerned with fuzzy entropy definition used for image segmentation. The key problem associated with this method is to find the optimal parameter combination of membership function so that an image can be transformed into fuzzy domain with maximum fuzzy entropy. Then, we compare the improved artificial fish swarm algorithm with other artificial intelligence models. The experiment indicates that the proposed method is quite effective and ubiquitous.

Keywords

artificial intelligence; entropy; fuzzy set theory; image segmentation; particle swarm optimisation; artificial intelligence model; fuzzy entropy definition; image segmentation; improved artificial fish swarm algorithm; membership function; optimal parameter algorithm; optimal parameter combination; Artificial intelligence; Automation; Conference management; Entropy; Image segmentation; Information management; Information technology; Marine animals; Pixel; Technology management; artificial fish swarm algorithm; image segmentation; maximum fuzzy entropy; membership function; optimal parameter;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Information Technology and Management Engineering, 2009. FITME '09. Second International Conference on

Conference_Location

Sanya

Print_ISBN

978-1-4244-5339-9

Type

conf

DOI

10.1109/FITME.2009.50

Filename

5380900