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), CBLU, University of Leeds
* revised and updated by: Marcus Hennecke, Ross Moore, Herb Swan
* with significant contributions from:
Jens Lippmann, Marek Rouchal, Martin Wilck and others -->
III. Automatic extraction for millions of galaxies
G. Paturel -
Y. Fang -
C. Petit -
R. Garnier -
J. Rousseau
Send offprint request: G. Paturel
CRAL-Observatoire de Lyon, F-69561 Saint-Genis Laval Cedex, France
Received February 17; accepted June 16, 2000
Abstract:
This paper presents a method for extracting a catalogue of
galaxy candidates from the Digitized Sky Survey (DSS).
The method is based on a functional analysis applied on each individual
plate. The standard deviation of pixel optical densities
versus the inverse of surface area leads to a diagram in which extended
and star-like objects are well separated. This diagram is
used for a preliminary recognition.
Then, a filtering process is applied using a Neural Network method associated
with a training sample built with well identified objects.
The main catalogue gives coordinates, total magnitude,
isophotal diameter, axis ratio, position angle for
galaxy
candidates.
The method favors the detection of normal galaxies. This creates a
bias against compact high surface brightness galaxies.
Key words: galaxies -- catalogues -- data analysis