QIU Shi, TANG Ying, ZHANG Wenbo, FENG Jun, ZHANG Fuchun, LI Chen. The Motion Planets Detection and Tracking Algorithm Based on Gestalt Principle[J]. Chinese Journal of Electronics, 2018, 27(4): 808-812. doi: 10.1049/cje.2017.11.006
Citation: QIU Shi, TANG Ying, ZHANG Wenbo, FENG Jun, ZHANG Fuchun, LI Chen. The Motion Planets Detection and Tracking Algorithm Based on Gestalt Principle[J]. Chinese Journal of Electronics, 2018, 27(4): 808-812. doi: 10.1049/cje.2017.11.006

The Motion Planets Detection and Tracking Algorithm Based on Gestalt Principle

doi: 10.1049/cje.2017.11.006
Funds:  This work is supported by CAS "Light of West China" Program (No.XAB2016B23), the Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences (No.LSIT201717G), the "Modern Information Detection and Intelligent Processing" Subject Construction of Chengdu University of Technology, and the National Natural Science Foundation of China (No.61501357).
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  • Corresponding author: TANG Ying (corresponding author) received the M.S. degree from University of Electronic Science and Technology of China. She is now an associate professor in Chengdu University of Technology. Her main research interest focuses on embedded technology. (Email:tangying@mail.cdut.edu.cn)
  • Received Date: 2016-12-08
  • Rev Recd Date: 2017-03-17
  • Publish Date: 2018-07-10
  • The moving planets have a few of pixels which can lead to lacking enough image characteristics when tracking them. So we propose the motion planets detection and tracking algorithm based on gestalt principle. We structure Gaussian mixture model to detect the motion area from the visual cognition perspective, and use astronomy images graphics characteristics to confirm the planet position. Then we propose space-time fusion model for tracking planet. All the experiments use 1000 16-bitframe images of wide view CCD camera which contain 5684 motion planets in total. The results show that our algorithm reaches an accuracy of 94% and has robustness.
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