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Proceedings Paper

Simulated ship recognition using two-dimensional PCA
Author(s): Guangzhou Zhao; Guangxi Zhu; Feng Peng; Shuwen Wang; Huazhong Xu
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Paper Abstract

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the two-dimensional Principal Component Analysis (2DPCA) method. The three-dimensional ship models achieve by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The 2DPCA method as against conventional PCA method for simulated ship recognition using training and testing experiments, as the training and testing sample size is large, and there are great variations in different azimuth and elevation for ship viewpoints. The experiment of ship recognition using the global feature of ships is not satisfied with us, so we proposed an improved 2DPCA method based on the local feature of ships. Some recognition results from simulated data are presented, it shows that the improved 2DPCA method outperform PCA in ship recognition and also superior to PCA in terms of computational efficiency for feature extraction. So our method is more preferable for ship classification and recognition.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678622 (15 November 2007); doi: 10.1117/12.749331
Show Author Affiliations
Guangzhou Zhao, Huazhong Univ. of Science and Technology (China)
Wuhan Univ. of Technology (China)
Guangxi Zhu, Huazhong Univ. of Science and Technology (China)
Feng Peng, Wuhan Univ. of Science and Technology (China)
Shuwen Wang, Radar Academy (China)
Huazhong Xu, Wuhan Univ. of Technology (China)

Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
Tianxu Zhang; Tianxu Zhang; Carl Anthony Nardell; Carl Anthony Nardell; Hanqing Lu; Duane D. Smith; Hangqing Lu, Editor(s)

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