DocumentCode
3305516
Title
GLCM and Fuzzy Clustering for Ocean Features Classification
Author
Tao, Ronghua ; Chen, Jie ; Chen, Biao ; Liu, Cuihua
fYear
2010
fDate
24-25 April 2010
Firstpage
538
Lastpage
540
Abstract
since Seasat lunched in 1978, much understanding has been gained on the potential of synthetic aperture radar (SAR) technology in oceanography. In this paper, the ocean features, i.e., internal waves, ocean fronts, present in SAR images are discussed. A new method for segmentation of SAR images is presented based on statistics of gray level co-occurrence matrix (GLCM) and the fuzzy C-Means clustering. The experimental results demonstrate its utility in the classification of various ocean features.
Keywords
Computer vision; Image segmentation; Machine vision; Man machine systems; Marine vehicles; Oceans; Pixel; Sea surface; Statistics; Surface acoustic waves; Fuzzy clustering; GLCM; Ocean feature;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location
Kaifeng, China
Print_ISBN
978-1-4244-6595-8
Electronic_ISBN
978-1-4244-6596-5
Type
conf
DOI
10.1109/MVHI.2010.29
Filename
5532608
Link To Document