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This paper presents and discusses the results of basic source finding tests in three dimensions (using spectroscopic data cubes) with duchamp, the standard source finder for the Australian Square Kilometre Array Pathfinder. For this purpose, we generated different sets of unresolved and extended Hi model sources. These models were then fed into duchamp, using a range of different parameters and methods provided by the software. The main aim of the tests was to study the performance of duchamp on sources with different parameters and morphologies and assess the accuracy of duchamp's source parametrisation. Overall, we find duchamp to be a powerful source finder capable of reliably detecting sources down to low signal-to-noise ratios and accurately measuring their position and velocity. In the presence of noise in the data, duchamp's measurements of basic source parameters, such as spectral line width and integrated flux, are affected by systematic errors. These errors are a consequence of the effect of noise on the specific algorithms used by duchamp for measuring source parameters in combination with the fact that the software only takes into account pixels above a given flux threshold and hence misses part of the flux. In scientific applications of duchamp these systematic errors would have to be corrected for. Alternatively, duchamp could be used as a source finder only, and source parametrisation could be done in a second step using more sophisticated parametrisation algorithms. This paper discusses the results of basic source finding tests with the duchamp source finder on different source models. We find duchamp to be a powerful source finder, capable of reliably detecting sources down to low signal-to-noise ratios. duchamp's measurements of basic source parameters, however, are affected by systematic errors. [ABSTRACT FROM AUTHOR]

The spectral line datacubes obtained from the Square Kilometre Array (SKA) and its precursors, such as the Australian SKA Pathfinder (ASKAP), will be sufficiently large to necessitate automated detection and parametrisation of sources. Matched filtering is widely acknowledged as the best possible method for the automated detection of sources. This paper presents the Characterised Noise Hi (cnhi) source finder, which employs a novel implementation of matched filtering. This implementation is optimised for the 3-D nature of the Hi spectral line observations of the planned Wide-field ASKAP Legacy L-band All-sky Blind surveY (WALLABY). The cnhi source finder also employs a novel sparse representation of 3-D objects, with a high compression rate, to implement the Lutz one-pass algorithm on datacubes that are too large to process in a single pass. WALLABY will use ASKAP's phenomenal 30 square degree field of view to image ~70% of the sky. It is expected that WALLABY will find 500 000 Hi galaxies out to z ~ 0.2. The Characterised Noise Hi source finder uses a novel approach to find sources in Hi spectral line datacubes using matched filtering. The concept, initial implementation and testing are presented here. [ABSTRACT FROM AUTHOR]