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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).
We present the Morphology-Density and Morphology-Radius relations (T-Sigma and T-R, respectively) obtained from the WINGS database of galaxies in nearby clusters. Aiming to achieve the best statistics, we exploit the whole sample of galaxies brighter
Massive quiescent galaxies at z>1 have been found to have small physical sizes, hence to be superdense. Several mechanisms, including minor mergers, have been proposed for increasing galaxy sizes from high- to low-z. We search for superdense massive
[Abridged] To effectively investigate galaxy formation and evolution, it is of paramount importance to exploit homogeneous data for large samples of galaxies in different environments. The WINGS (WIde-field Nearby Galaxy-cluster Survey) project aim i
We study the color-magnitude red sequence and blue fraction of 72 X-ray selected galaxy clusters at z=0.04-0.07 from the WINGS survey, searching for correlations between the characteristics of the red sequence and the environment. We consider the slo
We present the analysis of the emission line galaxies members of 46 low redshift (0.04 < z < 0.07) clusters observed by WINGS (WIde-field Nearby Galaxy cluster Survey, Fasano et al. 2006). Emission line galaxies were identified following criteria tha