Classifying auroras using artificial neural networks

Peter Rydesater; Urban Brandstrom; Ake Steen; Bjorn Gustavsson

doi:10.1117/12.343029

22 March 1999 Classifying auroras using artificial neural networks

Peter Rydesater, Urban Brandstrom, Ake Steen, Bjorn Gustavsson

Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343029
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden

Abstract

In Auroral Large Imaging System (ALIS) there is need of stable methods for analysis and classification of auroral images and images with for example mother of pearl clouds. This part of ALIS is called Selective Imaging Techniques (SIT) and is intended to sort out images of scientific interest. It's also used to find out what and where in the images there is for example different auroral phenomena's. We will discuss some about the SIT units main functionality but this work is mainly concentrated on how to find auroral arcs and how they are placed in images. Special case have been taken to make the algorithm robust since it's going to be implemented in a SIT unit which will work automatic and often unsupervised and some extends control the data taking of ALIS. The method for finding auroral arcs is based on a local operator that detects intensity differens. This gives arc orientation values as a preprocessing which is fed to a neural network classifier. We will show some preliminary results and possibilities to use and improve this algorithm for use in the future SIT unit.

Citation Download Citation

Peter Rydesater, Urban Brandstrom, Ake Steen, and Bjorn Gustavsson "Classifying auroras using artificial neural networks", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343029

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