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Proceedings Paper

Research on feature recognition algorithm for space target
Author(s): Jian Zhang; Xiaodong Zhou
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Paper Abstract

In this paper, a robust methodology on space target feature recognition is introduced. Aiming at area space target, its invariant features about geometry, affine transform and gray-level changing are extracted. Using the Backpropagation Fuzzy Neural Network (BPFNN) classifier, different models of target are classified and recognized. Aiming at point space target, firstly, local gray-level probability is computed and used to separate target and stars from background by setting threshold. Then by using multi-frame image accumulation, the contrast between target and stars is enhanced. Finally, target's accurate coordination has been achieved through centroid method with gray-level weighted. It has been improved that algorithm adopted in this study can reach approximately 93% accuracy of recognition for area target and 0.1 pixel of positioning accuracy for point target.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678616 (15 November 2007); doi: 10.1117/12.747790
Show Author Affiliations
Jian Zhang, Naval Aeronautical Engineering Institute (China)
Xiaodong Zhou, Naval Aeronautical Engineering Institute (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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