Object Classification in Astronomical Images

  • Richard L. White


Automated classification methods are needed for processing the huge quantities of data generated by modern astronomical instruments. The star-galaxy classification problem and some techniques that have been applied to it are briefly reviewed. Methods for constructing training sets and selecting parameters are described.

A new method of scaling parameter values using ranks has been developed. This approach is found to be of great utility for distinguishing stars and galaxies on digitized photographic plates. It should be widely applicable to other classification problems, especially when the data being classified are not completely homogeneous.


Decision Tree Object Classification Neural Network Method Photographic Plate Decision Tree Classifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media New York 1997

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  • Richard L. White

There are no affiliations available

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