An image database

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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.

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