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Proceedings Paper

A new ground plane detection method based on continuous multi-frame images and hierarchical screening
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Paper Abstract

Aircraft is a kind of valuable military equipment and transportation, so using target detection technology to detect ground aircraft in the optical remote sensing image has important research and application value. Although some achievements have been made in the relevant research, how to realize fast and effective ground aircraft target detection is still a challenging task because of the complex background of remote sensing image, large scale change and small imaging size, etc. Aiming at the application scenarios of multi-frame imaging, such as embedded detection and tracking system, this thesis proposes an aircraft target detection scheme based on hierarchical screening, which can improve the detection speed and reduce false alarm. Firstly, by analyzing the background characteristics, a target candidate region extraction method based on gray variance is adopted, and the acceleration is realized by integrating graph and shared computation. Then, the haar-like features are extracted in the candidate regions, which are then classified by the cascade AdaBoost classifier. Afterwards, a union-find-sets algorithm is used to merge the redundancy detection results and evaluate the confidence. Finally, the inter-frame correlation information is used to remove the false alarm. And we carried out experimental verification and proved the effectiveness of the algorithm.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 1143021 (14 February 2020); doi: 10.1117/12.2541930
Show Author Affiliations
Bin Zhou, Beijing Aerospace Automatic Control Institute (China)
Songzhi Jin, Beijing Aerospace Automatic Control Institute (China)
Yanxin Liu, Beijing Aerospace Automatic Control Institute (China)
Mengxi Hao, Beijing Aerospace Automatic Control Institute (China)
Hui Zhang, Beijing Aerospace Automatic Control Institute (China)

Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

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