The University of Southampton
University of Southampton Institutional Repository

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

Savolainen, T., Whiter, D.K. and Partamies, N. (2016) Automatic segmentation and classification of seven-segment display digits on auroral images Geoscientific Instrumentation, Methods and Data Systems, 5, pp. 305-314. (doi:10.5194/gi-5-305-2016).

Record type: Article


In this paper we describe a new and fully automatic method for segmenting and classifying digits in seven-segment displays. The method is applied 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. The digitised film images of the night sky contain valuable scientific information but are impractical to use without an automatic method for extracting the date–time from the display. We describe the implementation and the results of such a method in detail in this paper

PDF gi-5-305-2016.pdf - Version of Record
Available under License Other.
Download (1MB)

More information

Accepted/In Press date: 1 July 2016
Published date: 21 July 2016
Organisations: Astronomy Group


Local EPrints ID: 398309
ISSN: 2193-0856
PURE UUID: cfadc472-b395-4339-9003-ca7f75e3ff92
ORCID for D.K. Whiter: ORCID iD

Catalogue record

Date deposited: 22 Jul 2016 08:29
Last modified: 17 Jul 2017 18:31

Export record



Author: T. Savolainen
Author: D.K. Whiter ORCID iD
Author: N. Partamies

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.