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Automatic Solar Flare Tracking Using Image-Processing Techniques

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Abstract

Measurement of the evolution properties of solar flares through their complete cyclic development is crucial in the studies of Solar Physics. From the analysis of solar Hα images, we used Support Vector Machines (SVMs) to automatically detect flares and applied image segmentation techniques to compute their properties. We also present a solution for automatically tracking the apparent separation motion of two-ribbon flares and measuring their moving direction and speed in the magnetic fields. From these measurements, with certain assumptions, we inferred the reconnection of the electric field as a measure of the rate of the magnetic reconnection in the corona. The automatic procedure is a valuable tool for real-time monitoring of flare evolution.

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Authors and Affiliations

  1. College of Computing Sciences, New Jersey Institute of Technology, Newark, NJ , 07102, U.S.A

    Ming Qu & Frank Shih

  2. Center for Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ , 07102, U.S.A

    Ju Jing & Haimin Wang

  3. Big Bear Solar Observatory, New Jersey Institute of Technology, 40386 North Shore Lane, Big Bear City, CA , 92314, U.S.A

    Ju Jing

Authors
  1. Ming Qu
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  2. Frank Shih
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  3. Ju Jing
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  4. Haimin Wang
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Qu, M., Shih, F., Jing, J. et al. Automatic Solar Flare Tracking Using Image-Processing Techniques. Solar Physics 222, 137–149 (2004). https://doi.org/10.1023/B:SOLA.0000036879.72274.68

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  • DOI: https://doi.org/10.1023/B:SOLA.0000036879.72274.68

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