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Proceedings Paper

A new method for ship classification and recognition
Author(s): Guangzhou Zhao; Fei Wang; Tianxu Zhang
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Paper Abstract

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

Paper Details

Date Published: 4 November 2005
PDF: 8 pages
Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 604416 (4 November 2005); doi: 10.1117/12.655101
Show Author Affiliations
Guangzhou Zhao, Huazhong Univ. of Science and Technology (China)
State Key Lab. for Image Processing and Intelligent Control (China)
Fei Wang, Huazhong Univ. of Science and Technology (China)
State Key Lab. for Image Processing and Intelligent Control (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)
State Key Lab. for Image Processing and Intelligent Control (China)


Published in SPIE Proceedings Vol. 6044:
MIPPR 2005: Image Analysis Techniques
Deren Li; Hongchao Ma, Editor(s)

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