Active closure: symbolic active contour for spatial automated reasoning

Reducing the gap between quantitative visual data and qualitative spatial information such as qualitative spatial relations (QSR) is crucial for many intelligent and autonomous systems (AS) requiring the automated analysis of complex, visual scenes containing multiple objects of interest. Hence, our paper proposes to directly relate symbolic spatial knowledge to computer-vision concepts, in particular, to a new active-contour-based, symbolic concept. Indeed, active contours are deformable curves that evolve under forces computed from geometric and photometric properties of visual objects in order to delineate these target objects’ shapes. The active contours could not only be applied to generate the quantitative visual data related to the extracted objects of interest, but the computation of these active contours’ centroids could also be used to define centers of reference which are necessary for the determination of our spatial directional relations and projective relations among the objects of interest. In particular, this paper introduces the use of active contours to intrinsically define objects-of-interest’s closure which is useful for our spatial topological relations, leading to the symbolic active closure concept. This presented symbolic AI approach for qualitative spatial reasoning based on active contours has been successfully validated on geographical-related imagery, while being reliable, explainable, and sustainable.