  A theoretical and experimental analysis related to the identification of
vertices of unknown shapes is presented. Shapes are seen as real functions of
their closed boundary. Unlike traditional approaches, which see curvature as
the rate of change of the tangent to the curve, an alternative global
perspective of curvature is examined providing insight into the process of
noise-enabled vertex localization. The analysis leads to a paradox, that
certain vertices can be localized better in the presence of noise. The concept
of noising is thus considered and a relevant global method for localizing
"Global Vertices" is investigated. Theoretical analysis reveals that induced
noise can help localizing certain vertices if combined with global descriptors.
Experiments with noise and a comparison to localized methods validate the
theoretical results.
