SIMBAD references

We present an extended morphometric system to automatically classify galaxies from astronomical images. The new system includes the original and modified versions of the CASGM coefficients (Concentration C₁, Asymmetry A₃, and Smoothness S₃), and the new parameters entropy, H, and spirality σ_ψ. The new parameters A₃, S₃, and H are better to discriminate galaxy classes than A₁, S₁, and G, respectively. The new parameter σ_ψ captures the amount of non-radial pattern on the image and is almost linearly dependent on T-type. Using a sample of spiral and elliptical galaxies from the Galaxy Zoo project as a training set, we employed the Linear Discriminant Analysis (LDA) technique to classify EFIGI (Baillard et al. 4458 galaxies), Nair & Abraham (14,123 galaxies), and SDSS Legacy (779,235 galaxies) samples. The cross-validation test shows that we can achieve an accuracy of more than 90% with our classification scheme. Therefore, we are able to define a plane in the morphometric parameter space that separates the elliptical and spiral classes with a mismatch between classes smaller than 10%. We use the distance to this plane as a morphometric index (M_i) and we show that it follows the human based T-type index very closely. We calculate morphometric index M_i for ∼780k galaxies from SDSS Legacy Survey-DR7. We discuss how M_icorrelates with stellar population parameters obtained using the spectra available from SDSS-DR7.