  In recent years two sets of planar (2D) shape attributes, provided with an
intuitive physical meaning, were proposed to the remote sensing community by,
respectively, Nagao & Matsuyama and Shackelford & Davis in their seminal works
on the increasingly popular geographic object based image analysis (GEOBIA)
paradigm. These two published sets of intuitive geometric features were
selected as initial conditions by the present R&D software project, whose
multi-objective goal was to accomplish: (i) a minimally dependent and maximally
informative design (knowledge/information representation) of a general purpose,
user and application independent dictionary of 2D shape terms provided with a
physical meaning intuitive to understand by human end users and (ii) an
effective (accurate, scale invariant, easy to use) and efficient implementation
of 2D shape descriptors. To comply with the Quality Assurance Framework for
Earth Observation guidelines, the proposed suite of geometric functions is
validated by means of a novel quantitative quality assurance policy, centered
on inter feature dependence (causality) assessment. This innovative
multivariate feature validation strategy is alternative to traditional feature
selection procedures based on either inductive data learning classification
accuracy estimation, which is inherently case specific, or cross correlation
estimation, because statistical cross correlation does not imply causation. The
project deliverable is an original general purpose software suite of seven
validated off the shelf 2D shape descriptors intuitive to use. Alternative to
existing commercial or open source software libraries of tens of planar shape
functions whose informativeness remains unknown, it is eligible for use in
(GE)OBIA systems in operating mode, expected to mimic human reasoning based on
a convergence of evidence approach.
