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Proceedings Paper

An approach for in-harbor ship detection in complex background
Author(s): Tuo Li; Zhiguo Cao; Xing Li
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Paper Abstract

Aiming at the problem of in-harbor ship detection in forward-looking infrared image, this paper proposes a method for ship segmentation and false alarm suppressing based on k-means clustering segmentation. We obtain the simulated model images from visible satellite images and perspective relations. And the harbor area is determined by matching with HOG features. Then we segment the ship out of the harbor area. In order to suppress the false alarm, we apply k-means clustering segmentation to get the ship and the sea area simultaneously. By calculating the external convex polygon, we get rid of the false alarm targets. Experimental results suggest that our method has high detection accuracies and low false alarm rate.

Paper Details

Date Published: 26 October 2013
PDF: 8 pages
Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891809 (26 October 2013); doi: 10.1117/12.2031028
Show Author Affiliations
Tuo Li, Huazhong Univ. of Science and Technology (China)
Zhiguo Cao, Huazhong Univ. of Science and Technology (China)
Xing Li, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8918:
MIPPR 2013: Automatic Target Recognition and Navigation
Tianxu Zhang; Nong Sang, Editor(s)

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