Local and Global Analysis
Basically, only two approaches toward segmentation can be differentiated.
Since we are dealing with features f(x) given over some input
space 
, a single element of the dataset has two distinct properties: a value
f and a spatial coordinate x. Depending on the feature quality
used, we can distinguish two different ansätze for segmentation, called
in the following global and local analysis. In a global analysis, one ignores
metrical information, in a local analysis, one uses it. As we will see,
both types of segmentation are closely connected with two complementary
properties of objects: objects defined as prominent signal variations versus
objects defined by being encircled with borders.