Solar Filament Detection using Mask R-CNN

Rian Pramudia Salasa, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many algorithms have been proposed to detect solar filaments from H-Alpha images automatically, most of them use intensity thresholding method which requires intensity normalization. We propose a fast, automatic, and efficient method to detect filaments on H-Alpha images without carrying out intensity normalization using Mask R-CNN. The proposed method was applied on H-Alpha images obtained from Indonesian National Institute of Aeronautics and Space (LAPAN), resulting 96% precision. The average detection speed is 0.42 seconds per image. The method can be extended to perform detection on other solar features, such as sunspots, flares, and prominences.

Original languageEnglish
Title of host publication2019 International Workshop on Big Data and Information Security, IWBIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-71
Number of pages5
ISBN (Electronic)9781728153476
DOIs
Publication statusPublished - Oct 2019
Event2019 International Workshop on Big Data and Information Security, IWBIS 2019 - Bali, Indonesia
Duration: 11 Oct 2019 → …

Publication series

Name2019 International Workshop on Big Data and Information Security, IWBIS 2019

Conference

Conference2019 International Workshop on Big Data and Information Security, IWBIS 2019
CountryIndonesia
CityBali
Period11/10/19 → …

Keywords

  • automatic detection
  • filament detection
  • solar filament
  • solar image

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