SIMBAD references

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 2 772 061 galaxy candidates. The method favors the detection of normal galaxies. This creates a bias against compact high surface brightness galaxies.