Near Sets. Toward Approximation Space-Based Object Recognition

摘要

The problem considered in this paper is how to recognize objects that are qualitatively but not necessarily spatially near each other. The term qualitatively near is used here to mean closeness of descriptions or distinctive characteristics of objects. The solution to this problem is inspired by the work of Zdzislaw Pawlak during the early 1980s on the classification of objects by means of their attributes. In working toward a solution of the problem of the approximation of sets that are qualitatively near each other, this article considers an extension of the basic model for approximation spaces. The basic approach to object recognition is to consider the degree of overlap between families of perceptual neighbourhoods and a set of objects representing a standard. The proposed approach to object recognition includes a refinement of the generalized model for approximation spaces. This is a natural extension of recent work on nearness of objects. A byproduct of the proposed object recognition method is what we call a near set. The contribution of this article is an approximation space-based approach to object recognition formulated in the context of near sets.