Moving targets detection based on the 1-norm of the optical flow difference vector

Tongsheng Shen; Chunxin Wang; Yuye Zhang

doi:10.1117/12.746983

15 November 2007 Moving targets detection based on the 1-norm of the optical flow difference vector

Tongsheng Shen, Chunxin Wang, Yuye Zhang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67860U (2007) https://doi.org/10.1117/12.746983
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

With the development of space field, knowing and mastering the status of all kinds of space targets is necessary means to use the space resource efficiently. Moving targets detection is very important to mastering the status of the space targets by using the sequence space images since it is the precondition and basic of targets identify. Traditional method of moving targets detection which through the movement compensation is mainly faced to the linear moving of the background and seldom focus the research on the rolling moving around the center of the view field. This paper analysis the movement rule of targets and background stars in the sequence images and propose a moving targets detection method with the circumrotate moving background around the center of the view field based on the cumulate 1-norm of the optical flow difference vector. The first step is to get moving streak of targets and stars by the cumulate 1-norm of the optical flow difference vector. The second step is to find the entire moving point region by analysis moving streak and then detect targets. At the end, we examine the method by processing a sequence images, the result shows that the method is useful to the space targets detection.

Citation Download Citation

Tongsheng Shen, Chunxin Wang, and Yuye Zhang "Moving targets detection based on the 1-norm of the optical flow difference vector", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67860U (15 November 2007); https://doi.org/10.1117/12.746983

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