NDLI: A Hybrid System for Learning Sunspot Recognition and Classification

Content Provider	IEEE Xplore Digital Library
Author	Trung Thanh Nguyen Willis, C.P. Paddon, D.J. Hung Son Nguyen
Copyright Year	2006
Description	Author affiliation: Warsaw University, Warszawa, Poland (Hung Son Nguyen) \|\| University of Bath, UK (Trung Thanh Nguyen; Willis, C.P.; Paddon, D.J.)
Abstract	Sunspots observation and classification are important tasks for solar astronomers. The activity of sunspots can give clues to the timing of solar flares and the solar weather in general. This paper describes a hybrid system for automatic sunspot recognition and classification. The system uses a combination of image processing and machine learning techniques to process and classify sunspot groups from digital satellite images. Sunspot data are extracted from daily images of the solar disk captured by the NASA SOHO/MDI satellite. The classification scheme attempted was the seven-class Modified Zurich scheme. The main components of the hybrid system are: 1) the image processor, 2) the feature extractor, 3) the clusterer, 4) the classification learner. Furthermore, the paper compares two clustering algorithms: hierarchical average-link and a density-based DBSCAN and examines their usefulness in dealing with sunspot data. The aim is to create clusters that closely match "natural" sunspot groups. Clustering is an important step in the process as the classification performance is dependent on it. In previous papers we have shown that by combining clustering with classification the overall results can be substantially improved.
Sponsorship	IEEE Comput. Soc
Starting Page	257
Ending Page	264
File Size	576118
Page Count	8
File Format	PDF
ISBN	0769526748
DOI	10.1109/ICHIT.2006.253620
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-09
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Computer science Satellites Image processing NASA Clustering algorithms Rough sets Data mining Decision trees Sun
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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