Journal of The Korean Astronomical Society (천문학회지)

The Korean Astronomical Society (한국천문학회)
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AUTOMATIC DETECTION AND EXTRACTION ALGORITHM OF INTER-GRANULAR BRIGHT POINTS

  • Feng, Song (Computer Technology Application Key Lab of Yunnan Province and Faculty of Information Engineering and Automation, Kunming University of Science and Technology) ;
  • Ji, Kai-Fan (Computer Technology Application Key Lab of Yunnan Province and Faculty of Information Engineering and Automation, Kunming University of Science and Technology) ;
  • Deng, Hui (Computer Technology Application Key Lab of Yunnan Province and Faculty of Information Engineering and Automation, Kunming University of Science and Technology) ;
  • Wang, Feng (Computer Technology Application Key Lab of Yunnan Province and Faculty of Information Engineering and Automation, Kunming University of Science and Technology) ;
  • Fu, Xiao-Dong (Computer Technology Application Key Lab of Yunnan Province and Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
  • Received : 2012.08.31
  • Accepted : 2012.11.15
  • Published : 2012.12.31
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Abstract

Inter-granular Bright Points (igBPs) are small-scale objects in the Solar photosphere which can be seen within dark inter-granular lanes. We present a new algorithm to automatically detect and extract igBPs. Laplacian and Morphological Dilation (LMD) technique is employed by the algorithm. It involves three basic processing steps: (1) obtaining candidate "seed" regions by Laplacian; (2) determining the boundary and size of igBPs by morphological dilation; (3) discarding brighter granules by a probability criterion. For validating our algorithm, we used the observed samples of the Dutch Open Telescope (DOT), collected on April 12, 2007. They contain 180 high-resolution images, and each has a $85{\times}68\;arcsec^2$ field of view (FOV). Two important results are obtained: first, the identified rate of igBPs reaches 95% and is higher than previous results; second, the diameter distribution is $220{\pm}25km$, which is fully consistent with previously published data. We conclude that the presented algorithm can detect and extract igBPs automatically and effectively.

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References

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