Automatic recognition of sand wave topographic features based on optimally-directional profiling method

Zhou Jieqiong; Wu Ziyin; Zhao Dineng; Shang Jihong; Li Shoujun; Liang Yuyang; Zhou Mengjia

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Zhou Jieqiong, Wu Ziyin, Zhao Dineng, Shang Jihong, Li Shoujun, Liang Yuyang, Zhou Mengjia. Automatic recognition of sand wave topographic features based on optimally-directional profiling method[J]. Haiyang Xuebao, 2015, 37(7): 97-107.

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Automatic recognition of sand wave topographic features based on optimally-directional profiling method

1.
The Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou 310012, China
2.
Department of Earth Sciences, Zhejiang University, Hangzhou 310028, China

Received Date: 2014-11-06
Rev Recd Date: 2015-01-14

Abstract

Abstract

Sand wave is a widely occurring submarine bedform which exists on the sea floor of shallow seas due to the complex interaction between waves,tides and sediments. Knowledge of sand wave characteristics and behavior has scientific import and engineering application value. Crest lines and trough lines are basic topographic characteristics of sand wave,and the basis to describe sand wave variation. In this paper,we present a new method of automatic recognition of sand wave topographic features based on composite digital depth model (DDM),called optimally-directional profiling method. We built an optimal direction map from DDM,and use the optimal direction to profile DDM and involve matrix calculus,by verifying extrema points to extract the topographic features. Taking composite sand waves in Taiwan Bank as an example,the comparison experiment result indicated that,the method is capable of extracting crest lines and trough lines of sand waves automatically and accurately based on multi-resolution DDM. With no requirement for setting any thresholds,the automatic degree of extracting topographic features is further increased. The method possessed important practical application value.
- optimally-directional profiling method,
- digital depth model (DDM),
- eight neighborhood,
- sand wave,
- crest lines,
- trough lines,
- automatic recognition

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References(28)

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