A fast and effective segmentation algorithm for undersea hydrothermal vent image

Authors:
Fuyuan Peng;Qian Xia;Guohua Xu;Xi Yu;Lin Luo
Affiliations:
Electronic Information Engineering Department of Huazhong University of Science and Technology, Wuhan, China;Electronic Information Engineering Department of Huazhong University of Science and Technology, Wuhan, China;Traffic Science and Engineering College of Huazhong University of Science and Technology, Wuhan, China;Electronic Information Engineering Department of Huazhong University of Science and Technology, Wuhan, China;Electronic Information Engineering Department of Huazhong University of Science and Technology, Wuhan, China
Venue:
ISCGAV'04 Proceedings of the 4th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Year:
2004

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Abstract

This paper puts forward a segmentation algorithm for undersea hydrrothermal vent image. Basing on the in-depth analysis on the difference between sea-water area, rock and smoke area, which are the three kinds of objects in the typical undersea hydrothermal vent image, we employ both OTSU thresholding and Fuzzy C-Mean (FCM) clustering to segment the image, and discard all the non-interested area living only smoke area. Experiments show that this algorithm can segment the image both quickly and precisely.