Comparison of automatic methods to detect sunspots in the Coimbra Observatory spectroheliograms. (arXiv:2002.04270v1 [astro-ph.SR])
<a href="http://arxiv.org/find/astro-ph/1/au:+Carvalho_S/0/1/0/all/0/1">S. Carvalho</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Gomes_S/0/1/0/all/0/1">S. Gomes</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Barata_T/0/1/0/all/0/1">T. Barata</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Lourenco_A/0/1/0/all/0/1">A. Lourenco</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Peixinho_N/0/1/0/all/0/1">N. Peixinho</a>
The Astronomical Observatory of the University of Coimbra has a huge
collection of solar images, acquired daily since 1926. From the beginning, only
spectroheliograms in the CaiiK line has been recorded, and since 1989 in the
H_alpha line also. Such dataset requires efficient tools to detect and analyze
solar activity features. The objective of this work is to create a tool that
allows to automatic detect sunspots, umbra, and penumbra, that can be applied
to the entire dataset. To achieve this, two different approaches have been
developed, one based on mathematical morphology and another based on the
intensities of the digital levels of the pixels. Both approaches were applied
to a subset of images with features identified visually by an experimented
solar observer. The performance of both methods was compared through the
metrics Precision, Recall and F-score. Another evaluation was made based on the
catalogs from Heliophysics Features Catalog and the SILSO catalogue.
The Astronomical Observatory of the University of Coimbra has a huge
collection of solar images, acquired daily since 1926. From the beginning, only
spectroheliograms in the CaiiK line has been recorded, and since 1989 in the
H_alpha line also. Such dataset requires efficient tools to detect and analyze
solar activity features. The objective of this work is to create a tool that
allows to automatic detect sunspots, umbra, and penumbra, that can be applied
to the entire dataset. To achieve this, two different approaches have been
developed, one based on mathematical morphology and another based on the
intensities of the digital levels of the pixels. Both approaches were applied
to a subset of images with features identified visually by an experimented
solar observer. The performance of both methods was compared through the
metrics Precision, Recall and F-score. Another evaluation was made based on the
catalogs from Heliophysics Features Catalog and the SILSO catalogue.
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