  While automatic detection of point sources in astronomical images has
experienced a great degree of success, less effort has been directed towards
the detection of extended and low-surface brightness features. At present,
existing telescopes still rely on human expertise to reduce the raw data to
usable images and then to analyse the images for non-pointlike objects.
However, the next generation of radio telescopes will generate unprecedented
volumes of data making manual data reduction and object extraction infeasible.
Without developing new methods of automatic detection for extended and diffuse
objects such as supernova remnants, bent-tailed galaxies, radio relics and
halos, a wealth of scientifically important results will not be uncovered. In
this paper we explore the response of the Circle Hough Transform to a
representative sample of different extended circular or arc-like astronomical
objects. We also examine the response of the Circle Hough Transform to input
images containing noise alone and inputs including point sources.
