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The Detection of Multiple Dim Small Targets Based on Iterative Density Clustering and SURF Descriptor

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Web Information Systems Engineering – WISE 2015 (WISE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9419))

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Abstract

Following the classical TBD (Track before Detection) framework popular used in ATR (Automatic Target Recognition), a fast algorithm is proposed in this paper. Different from the classical data association methods, the extraction of target trajectory is converted into clustering process of searching density peaks. At first, the 3D time sequence is projected into 2D plane and then it is segmented into multiple zones either targets or clutter. Finally, the target trace is discriminated further by continuous and consistency constraints. During preprocessing, in order to guarantee the sparse of the background and the intensive of the targets SURF (Speeded up Robust Features) detector is introduced. The experiments result shows that the algorithm can detect small targets with lower SCR both in cloudy sky and sea background, compared with most recent algorithms it has a priority in time complexity and false alarm suppression ratio.

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Acknowledgements

The work is supported by National Natural Science Foundation of China (No: 61303080) and Natural Science Foundation of Fujian Province, China (No: 2013J01249).

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Authors and Affiliations

  1. Software School of Xiamen University, Fujian, 361005, China

    Haiying Zhang & Yang Gao

  2. School of Computing and Information Sciences, Florida International University, Miami, FL, 33199, USA

    Tao Li

Authors
  1. Haiying Zhang
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  2. Yang Gao
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  3. Tao Li
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Corresponding author

Correspondence to Haiying Zhang .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jianyong Wang

  2. Poznan University of Economics, Poznan, Poland

    Wojciech Cellary

  3. Florida Atlantic University, Boca Raton, Florida, USA

    Dingding Wang

  4. Victoria University, Melbourne, Victoria, Australia

    Hua Wang

  5. Florida International University, Miami, Florida, Florida, USA

    Shu-Ching Chen

  6. Florida International University, Miami, Florida, USA

    Tao Li

  7. Victoria University, Melbourne, Victoria, Australia

    Yanchun Zhang

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Zhang, H., Gao, Y., Li, T. (2015). The Detection of Multiple Dim Small Targets Based on Iterative Density Clustering and SURF Descriptor. In: Wang, J., et al. Web Information Systems Engineering – WISE 2015. WISE 2015. Lecture Notes in Computer Science(), vol 9419. Springer, Cham. https://doi.org/10.1007/978-3-319-26187-4_25

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  • DOI: https://doi.org/10.1007/978-3-319-26187-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26186-7

  • Online ISBN: 978-3-319-26187-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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