Research on feature recognition algorithm for space target

Jian Zhang; Xiaodong Zhou

doi:10.1117/12.747790

15 November 2007 Research on feature recognition algorithm for space target

Jian Zhang, Xiaodong Zhou

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678616 (2007) https://doi.org/10.1117/12.747790
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Jian Zhang and Xiaodong Zhou "Research on feature recognition algorithm for space target", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678616 (15 November 2007); https://doi.org/10.1117/12.747790

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