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Proceedings Paper

Automatic ship target classification based on aerial images
Author(s): Jinhui Lan; Lili Wan
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Paper Abstract

As the important reconnaissance and offensive weapon in future battlefield, Micro Aerial Vehicle (MAV) is applied more and more widely in civil and military field. In the sea battlefield, ship classification applied to MAV could effectively realize signals collection, force protection and strike to ship targets. At present, methods of ship classification are mostly based on signals from radar, infrared or ultrasonic. However, because of large volume and complex equipments, these methods can't meet the requirement of MAV. Thus, ship classification based on visible sensor is chosen and it could solve volume and weight limits of MAV. In order to realize ship classification in MAV, ship classification based on aerial images is first proposed and an effective robust algorithm for classification based on modified Zernike moment invariants is proposed in this paper. The task of classification is that the ships are classified into two categories, aircraft carrier and chaser. The experimental results show that the correct classification rate is more than 92% and the algorithm proposed is effective to solve classification problem for ship targets in MAV.

Paper Details

Date Published: 28 January 2009
PDF: 10 pages
Proc. SPIE 7156, 2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments, 715612 (28 January 2009); doi: 10.1117/12.811434
Show Author Affiliations
Jinhui Lan, Univ. of Science and Technology Beijing (China)
Lili Wan, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 7156:
2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments
Yunlong Sheng; Yongtian Wang; Lijiang Zeng, Editor(s)

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