Abstract
This chapter gives a concise overview of the foundations of a perceptual near set approach to the discovery of affinities between perceptual objects and perceptual granules that provide a basis for perceptual systems useful in science and engineering. A perceptual object is something perceptible to the senses or knowable by the mind. Perceptual objects that have the same appearance are considered to be perceptually near each other, i.e., perceived objects that have perceived affinities or, at least, similar descriptions. A perceptual granule is a set of perceptual objects originating from observations of the objects in the physical world. Near set theory provides a basis for observation, comparison and classification of perceptual granules. By considering nearness relations in the context of a perceptual system, it is possible to gauge affinities (nearness) perceptual objects. Two kinds of indiscernibility relations and a tolerance relation make it possible to define various nearness relations. Examples of near images as perceptual systems are presented. The main contribution of this chapter is the introduction of a formal basis for discovering affinities between perceptual information granules.
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Peters, J.F., Ramanna, S. (2009). Affinities between Perceptual Granules: Foundations and Perspectives. In: Bargiela, A., Pedrycz, W. (eds) Human-Centric Information Processing Through Granular Modelling. Studies in Computational Intelligence, vol 182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92916-1_3
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DOI: https://doi.org/10.1007/978-3-540-92916-1_3
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