Segmentation of a sonar image from a small underwater target using the improved fuzzy clustering algorithm

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-leve...

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Vydáno v:2011 Second International Conference on Mechanic Automation and Control Engineering s. 5218 - 5220
Hlavní autoři: Haitao Guo, Jun Zhou, Ruili Song, Junpeng Wu
Médium: Konferenční příspěvek
Jazyk:čínština
angličtina
Vydáno: IEEE 01.07.2011
Témata:
Clustering algorithms
Computers
Educational institutions
Electrical engineering
fuzzy clustering
Histograms
Image segmentation
small underwater target
Sonar
sonar image
ISBN:1424494362, 9781424494361
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Shrnutí: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.
ISBN:1424494362
9781424494361
DOI:10.1109/MACE.2011.5988166