An approach for in-harbor ship detection in complex background

Tuo Li; Zhiguo Cao; Xing Li

doi:10.1117/12.2031028

26 October 2013 An approach for in-harbor ship detection in complex background

Tuo Li, Zhiguo Cao, Xing Li

Proceedings Volume 8918, MIPPR 2013: Automatic Target Recognition and Navigation; 891809 (2013) https://doi.org/10.1117/12.2031028
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

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.

Citation Download Citation

Tuo Li, Zhiguo Cao, and Xing Li "An approach for in-harbor ship detection in complex background", Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891809 (26 October 2013); https://doi.org/10.1117/12.2031028

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KEYWORDS

Image segmentation

Detection and tracking algorithms

Binary data

Satellites

Earth observing sensors

Satellite imaging

Forward looking infrared

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