Wavelet neural network identification and classification of sediment seabed sonar images based on genetic algorithms

Xiong Mingkuan; Wu Ziyin; Li Shoujun; Shang Jihong

doi:10.3969/j.issn.0253-4193.2014.05.010

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Xiong Mingkuan, Wu Ziyin, Li Shoujun, Shang Jihong. Wavelet neural network identification and classification of sediment seabed sonar images based on genetic algorithms[J]. Haiyang Xuebao, 2014, 36(5): 90-97. doi: 10.3969/j.issn.0253-4193.2014.05.010

Citation:

Xiong Mingkuan, Wu Ziyin, Li Shoujun, Shang Jihong. Wavelet neural network identification and classification of sediment seabed sonar images based on genetic algorithms[J]. Haiyang Xuebao, 2014, 36(5): 90-97. doi: 10.3969/j.issn.0253-4193.2014.05.010

Citation:

Xiong Mingkuan, Wu Ziyin, Li Shoujun, Shang Jihong. Wavelet neural network identification and classification of sediment seabed sonar images based on genetic algorithms[J]. Haiyang Xuebao, 2014, 36(5): 90-97. doi: 10.3969/j.issn.0253-4193.2014.05.010

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Wavelet neural network identification and classification of sediment seabed sonar images based on genetic algorithms

doi: 10.3969/j.issn.0253-4193.2014.05.010

Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China;Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou 310012, China

Received Date: 2013-04-28
Rev Recd Date: 2013-10-16

Abstract

Abstract

Segmenting the seafloor sonar gray image,and extracting characteristic vector unit with principal component analysis,the selection of the mean,standard deviation,contrast,correlation coefficient,energy and homogeneity is as training characteristic vector,to build wavelet neural network. Using genetic algorithm to optimize the wavelet neural network initial weights and wavelet parameters,the three of sediment types sand,rocks,mud were been training,and get three sediment test accuracy of 90% or more,far better than single wavelet neural network training test accuracy. Experiments show that wavelet neural network based on genetic algorithm can be effectively used for seabed sediment sonar image recognition and classification,and overcome that the wavelet neural network training shortcomings easy to fall into local minimum.
- genetic algorithm-wavelet neural network,
- sediment classification,
- sonar gray image,
- genetic algorithm,
- wavelet analysis

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References(24)

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