Paper
3 November 2005 A new method for ship classification and recognition
Author Affiliations +
Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 604416 (2005) https://doi.org/10.1117/12.655101
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guangzhou Zhao, Fei Wang, and Tianxu Zhang "A new method for ship classification and recognition", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 604416 (3 November 2005); https://doi.org/10.1117/12.655101
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Cited by 1 scholarly publication.
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KEYWORDS
Principal component analysis

3D modeling

Neural networks

Feature extraction

Databases

Detection and tracking algorithms

3D image processing

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