  A new method for the statistical analysis of 3D point processes, based on the
family of Minkowski functionals, is explained and applied to modelled galaxy
distributions generated by a toy-model and cosmological simulations of the
large-scale structure in the Universe. These measures are sensitive to both,
geometrical and topological properties of spatial patterns and appear to be
very effective in discriminating different point processes. Moreover by the
means of conditional subsampling, different building blocks of large-scale
structures like sheets, filaments and clusters can be detected and extracted
from a given distribution.
