Articles | Volume 5, issue 2
https://doi.org/10.5194/gi-5-305-2016
https://doi.org/10.5194/gi-5-305-2016
Research article
 | 
21 Jul 2016
Research article |  | 21 Jul 2016

Automatic segmentation and classification of seven-segment display digits on auroral images

Tuomas Savolainen, Daniel Keith Whiter, and Noora Partamies

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Cited articles

Bonačić, I., Herman, T., Krznar, T., Mangić, E., Molnar, G., and Čupić, M.: Optical Character Recognition of Seven-segment Display Digits Using Neural Networks, in: 32st International Convention on Information and Communication Technology, Electronics and Microelectronics, http://morgoth.zemris.fer.hr/people/Marko.Cupic/files/2009-SP-MIPRO.pdf, last access: 3 March 2015.
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Deng, L.: The MNIST database of handwritten digit images for machine learning research, IEEE Signal Proc. Mag., 29, 141–142, http://research.microsoft.com/pubs/204699/MNIST-SPM2012.pdf, last access: 13 June 2015.
Nevanlinna, H. and Pulkkinen, T. I.: Solar cycle correlations of substorm and auroral occurrence frequency, Geophys. Res. Lett., 25, 3087–3090, https://doi.org/10.1029/98GL02335, 1998.
Nevanlinna, H. and Pulkkinen, T. I.: Auroral observations in Finland: Results from all-sky cameras, 1973–1997, J. Geophys. Res., 106, 8109–8118, https://doi.org/10.1029/1999JA000362, 2001.
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Short summary
In this paper we describe a new method for recognition of digits in seven-segment displays. The method is used for adding date and time information to a dataset consisting of about 7 million auroral all-sky images taken during the time period of 1973–1997 at camera stations centred around Sodankylä observatory in Northern Finland. In each image there is a clock display for the date and time together with the reflection of the whole night sky through a spherical mirror.