Detection and tracking of multi-space junks in star images

Wenkang Deng; Zongxi Song

doi:10.1117/12.2244285

29 August 2016 Detection and tracking of multi-space junks in star images

Wenkang Deng, Zongxi Song

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100330N (2016) https://doi.org/10.1117/12.2244285
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

An algorithm of detection and tracking of multiple small moving space junks under the complex star sequential images is proposed in this paper. Firstly we take image smoothing and adaptive threshold segment to improve the weight of junks. Furthermore, back neighborhood frame correlation (BNFC) is proposed to detect and locate the junk which is sheltered by bigger interfaced stars. Through cross projection method, we could extract the centroid of the moving junks. At last, the Kalman Filter is used to track and estimate the trajectory of moving junks. Experiments show that through this algorithm the multiple small space junks could be detected and tracked effectively and accurately under complex star background with good performance in low error rate and good real-time processing.

Citation Download Citation

Wenkang Deng and Zongxi Song "Detection and tracking of multi-space junks in star images", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100330N (29 August 2016); https://doi.org/10.1117/12.2244285

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