Decision fusion fish identification using SVM and its experimental study

作者：Du, Weidong; Li, Haisen^*; Wei, Yukuo; Xu, Chao

来源：Journal of Harbin Engineering University, 2015, 36(5): 623-627.

DOI：10.3969/j.issn.1006-7043.201403083

• Decision fusion
• Discrete Cosine Transform(DCT)
• Fish identification
• Multi-azimuth
• Wavelet packet transform (WPT)

In order to meet the requirement of high precision for fish identification based on acoustic scattering data, an SVM-based multi-azimuth decision fusion method for acoustic scattering data is proposed in this study. Firstly, the wavelet packet transform (WPT) and discrete cosine transform (DCT) methods are used to extract features from multi-azimuth acoustic scattering data and the extracted features are processed for a dimension-reduction. Secondly, SVM classifiers are employed to make decisions for multiple times based on the features of each azimuth. Finally, the identification result is figured out as the ultimate output. In the experiment, three fishes are selected and the reliable scheme is designed to obtain multi-azimuth acoustic scattering data. The identification rates are demonstrated for each case of different azimuth numbers using the WPT and DCT methods. The theoretical analysis and processing results indicated that the overall identification rates show a rising trend as the azimuth number increases. The SVM-based multi-azimuth decision fusion method for acoustic scattering data can increase the identification rate to 90%.

• 出版日期2015
• 单位哈尔滨工程大学