Ant Colony Fuzzy Clustering Algorithm Applied to SAR Image Segmentation

Author

Chunmao, Li ; Lingzhi, Wang ; Shunjun, Wu

Author_Institution

Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´´an

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

A method of dynamic fuzzy clustering analysis based on ant colony algorithm for SAR image segmentation is proposed. The method confirms dynamically the clustering number and center by the stronger fuzzy clustering ability of ant colony algorithm. Texture feature of SAR image is calculated according to gray level co-occurrence matrix (GLCM), and the proper feature vector is selected through statistic analysis. The measurement SAR image segmentation experiment indicates that the algorithm can segment the target fast and exactly, and is an effective SAR image segmentation method

Keywords

feature extraction; fuzzy systems; image segmentation; image texture; matrix algebra; radar imaging; statistical analysis; synthetic aperture radar; GLCM; SAR image segmentation; ant colony algorithm; dynamic fuzzy clustering algorithm; gray level cooccurrence matrix; statistic analysis; synthetic aperture radar; texture feature; Algorithm design and analysis; Biochemistry; Clustering algorithms; Feedback; Heuristic algorithms; Image analysis; Image segmentation; Radar signal processing; Signal processing algorithms; Synthetic aperture radar; SAR image segmentation; ant colony algorithm; fuzzy clustering; gray level co-occurrence matrix;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343521

Filename

4148498