DocumentCode
2814375
Title
Segmentation of a sonar image from a small underwater target using the improved fuzzy clustering algorithm
Author
Guo, Haitao ; Zhou, Jun ; Song, Ruili ; Wu, Junpeng
Author_Institution
Electr. Eng. Coll., Northeast Dianli Univ., Jilin, China
fYear
2011
fDate
15-17 July 2011
Firstpage
5218
Lastpage
5220
Abstract
This paper expatiates on the improved fuzzy c-means (FCM) clustering algorithm. In the algorithm, the membership values are determined via the improved method, and the number of the centers of FCM clustering are determined via the number of the peaks of the two-dimensional histogram on the gray-level values of pixels and gradient values of pixel neighborhoods. The application to segmentation of a sonar image of a small underwater target shows that the improved FCM clustering algorithm can segment the image into the shadow and echo regions of the target, and that the improved algorithm is more intelligent and timesaving than the traditionary FCM clustering algorithm.
Keywords
fuzzy set theory; image segmentation; pattern clustering; sonar imaging; FCM clustering algorithm; fuzzy c-means clustering algorithm; gradient values; gray-level values; pixel neighborhoods; small underwater target; sonar image segmentation; two-dimensional histogram; Clustering algorithms; Computers; Educational institutions; Electrical engineering; Histograms; Image segmentation; Sonar; fuzzy clustering; image segmentation; small underwater target; sonar image;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
Conference_Location
Hohhot
Print_ISBN
978-1-4244-9436-1
Type
conf
DOI
10.1109/MACE.2011.5988166
Filename
5988166
Link To Document