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Proceedings Paper

Ship detection and classification from overhead imagery
Author(s): Heidi Buck; Elan Sharghi; Keith Bromley; Chessa Guilas; Tommy Chheng
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Paper Abstract

This paper presents a sequence of image-processing algorithms suitable for detecting and classifying ships from nadir panchromatic electro-optical imagery. Results are shown of techniques for overcoming the presence of background sea clutter, sea wakes, and non-uniform illumination. Techniques are presented to measure vessel length, width, and direction-of-motion. Mention is made of the additional value of detecting identifying features such as unique superstructure, weaponry, fuel tanks, helicopter landing pads, cargo containers, etc. Various shipping databases are then described as well as a discussion of how measured features can be used as search parameters in these databases to pull out positive ship identification. These are components of a larger effort to develop a low-cost solution for detecting the presence of ships from readily-available overhead commercial imagery and comparing this information against various open-source ship-registry databases to categorize contacts for follow-on analysis.

Paper Details

Date Published: 24 September 2007
PDF: 15 pages
Proc. SPIE 6696, Applications of Digital Image Processing XXX, 66961C (24 September 2007); doi: 10.1117/12.754019
Show Author Affiliations
Heidi Buck, SPAWAR Systems Ctr., San Diego (United States)
Elan Sharghi, SPAWAR Systems Ctr., San Diego (United States)
Keith Bromley, SPAWAR Systems Ctr., San Diego (United States)
Chessa Guilas, SPAWAR Systems Ctr., San Diego (United States)
Tommy Chheng, Univ. of California, San Diego (United States)

Published in SPIE Proceedings Vol. 6696:
Applications of Digital Image Processing XXX
Andrew G. Tescher, Editor(s)

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