Gradient Pattern Analysis Applied to Galaxy Morphology
  Gradient pattern analysis (GPA) is a well-established technique for measuring
gradient bilateral asymmetries of a square numerical lattice. This paper
introduces an improved version of GPA designed for galaxy morphometry. We show
the performance of the new method on a selected sample of 54,896 objects from
the SDSS-DR7 in common with Galaxy Zoo 1 catalog. The results suggest that the
second gradient moment, G2, has the potential to dramatically improve over more
conventional morphometric parameters. It separates early from late type
galaxies better (\sim 90\%) than the CAS system (C \sim 79\%, A \sim 50\%, S
\sim 43\%) and a benchmark test shows that it is applicable to hundreds of
thousands of galaxies using typical processing systems.
