Histogram based fuzzy Kohonen clustering network for image segmentation

Author

Atmaca, Hamdi ; Bulut, Mehmet ; Demir, Derya

Author_Institution

Dept. of Electr.-Electron., Dumlupinar Univ., Kutahya, Turkey

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

951

Abstract

A fuzzy Kohonen (1989) clustering network (FKCN) algorithm is proposed for image segmentation. Large image sizes are in general required for various types of imaging applications. For a large amount of data, computation of the FKCN algorithm for iterative operation will take a long time. Therefore, an attempt has been made to make the FKCN algorithm realistically useful for image segmentation. The proposed FKCN algorithm keeps its advantages, but instead of using the image space, a gray level function of the image was used for all imaging data. A new algorithm was developed which provided good results in the short time taken for image segmentation

Keywords

fuzzy systems; image segmentation; self-organising feature maps; algorithm; fuzzy Kohonen clustering network; gray level function; histogram; image segmentation; image size; imaging applications; imaging data; iterative operation; Clustering algorithms; Computer networks; Electronic mail; Histograms; Image segmentation; Iterative algorithms; Layout; Partitioning algorithms; Pattern recognition; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.561062

Filename

561062