  The scope of this paper is to compare the catalog extraction performances
obtained using the new combination of SExtractor with PSFEx, against the more
traditional and diffuse application of DAOPHOT with ALLSTAR; therefore, the
paper may provide a guide for the selection of the most suitable catalog
extraction software. Both software packages were tested on two kinds of
simulated images having, respectively, a uniform spatial distribution of
sources and an overdensity in the center. In both cases, SExtractor is able to
generate a deeper catalog than DAOPHOT. Moreover, the use of neural networks
for object classification plus the novel SPREAD\_MODEL parameter push down to
the limiting magnitude the possibility of star/galaxy separation. DAOPHOT and
ALLSTAR provide an optimal solution for point-source photometry in stellar
fields and very accurate and reliable PSF photometry, with robust star-galaxy
separation. However, they are not useful for galaxy characterization, and do
not generate catalogs that are very complete for faint sources. On the other
hand, SExtractor, along with the new capability to derive PSF photometry, turns
to be competitive and returns accurate photometry also for galaxies. We can
assess that the new version of SExtractor, used in conjunction with PSFEx,
represents a very powerful software package for source extraction with
performances comparable to those of DAOPHOT. Finally, by comparing the results
obtained in the case of a uniform and of an overdense spatial distribution of
stars, we notice, for both software packages, a decline for the latter case in
the quality of the results produced in terms of magnitudes and centroids.
