Citation:
Vahid Vahidpour,Amir Rastegarnia,Azam Khalili.An Automated Approach to Passive Sonar Classification Using Binary Image Features[J].Journal of Marine Science and Application,2015,(3):327-333.[doi:10.1007/s11804-015-1312-z]
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An Automated Approach to Passive Sonar Classification Using Binary Image Features
Vahid Vahidpour,Amir Rastegarnia,Azam Khalili.An Automated Approach to Passive Sonar Classification Using Binary Image Features[J].Journal of Marine Science and Application,2015,(3):327-333.[doi:10.1007/s11804-015-1312-z]
Info
- Title:
- An Automated Approach to Passive Sonar Classification Using Binary Image Features
- Author(s):
- Vahid Vahidpour; Amir Rastegarnia; Azam Khalili
- Affilations:
- Keywords:
- binary image; passive sonar; neural classifier; ship recognition; short-time Fourier transform; fractal-based method
- DOI:
- 10.1007/s11804-015-1312-z
- Abstract:
- This paper proposes a new method for ship recognition and classification using sound produced and radiated underwater. To do so, a three-step procedure is proposed. First, the preprocessing operations are utilized to reduce noise effects and provide signal for feature extraction. Second, a binary image, made from frequency spectrum of signal segmentation, is formed to extract effective features. Third, a neural classifier is designed to classify the signals. Two approaches, the proposed method and the fractal-based method are compared and tested on real data. The comparative results indicated better recognition ability and more robust performance of the proposed method than the fractal-based method. Therefore, the proposed method could improve the recognition accuracy of underwater acoustic targets.
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Memo
- Memo:
-
收稿日期:2014-12-8;改回日期:2015-3-23。
通讯作者:Amir Rastegarnia, E-mail:a_rastegar@ieee.org
