Morphology of galaxies in the WINGS clusters
  We present the morphological catalog of galaxies in nearby clusters of the
WINGS survey (Fasano et al. 2006). The catalog contains a total number of 39923
galaxies, for which we provide the automatic estimates of the morphological
type applying the purposely devised tool MORPHOT to the V-band WINGS imaging.
For ~3000 galaxies we also provide visual estimates of the morphological types.
A substantial part of the paper is devoted to the description of the MORPHOT
tool, whose application is limited, at least for the moment, to the WINGS
imaging only. The approach of the tool to the automation of morphological
classification is a non parametric and fully empiri- cal one. In particular,
MORPHOT exploits 21 morphological diagnostics, directly and easily computable
from the galaxy image, to provide two independent classifications: one based on
a Maximum Likelihood (ML), semi-analytical technique, the other one on a Neural
Network (NN) machine. A suitably selected sample of ~1000 visually clas- sified
WINGS galaxies is used to calibrate the diagnostics for the ML estimator and as
a training set in the NN machine. The final morphological estimator combines
the two techniques and proves to be effective both when applied to an
additional test sample of ~1000 visually classified WINGS galaxies and when
compared with small samples of SDSS galaxies visually classified by Fukugita et
al. (2007) and Nair et al. (2010). Finally, besides the galaxy morphology
distribution (corrected for field contamination) in the WINGS clusters, we
present the ellipticity ({\epsilon}), color (B-V) and Sersic index (n)
distributions for different morphological types, as well as the morphological
fractions as a function of the clustercentric distance (in units of R200).
