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

Multi-Objective Software Suite of Two-Dimensional Shape Descriptors for Object-Based Image Analysis