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Nearness of Visual Objects. Application of Rough Sets in Proximity Spaces

Peters J.F., Skowron A., Stepaniuk J.

Fundamenta Informaticae

2013

Vol. 128, nr 1-2

156--176

The problem considered in this paper is how to describe and compare visual objects. The solution to this problem stems from a consideration of nearness relations in two different forms of Efremovič proximity spaces. In this paper, the visual objects are picture elements in digital images. In particular, this problem is solved in terms of the application of rough sets in proximity spaces. The basic approach is to consider the nearness of the upper and lower approximation of a set introduced by Z. Pawlak during the early 1980s as a foundation for rough sets. Two forms of nearness relations are considered, namely, a spatial EF- and a descriptive EF-relation. This leads to a study of the nearness of objects either spatially or descriptively in the approximation of a set. The nearness approximation space model developed in 2007 is refined and extended in this paper, leading to new forms of nearness approximation spaces. There is a natural transition from the two forms of nearness relations introduced in this article to the study of nearness granules.

Classifying Visual Objects with the Consistency-Driven Pairwise Comparisons Method

Koczkodaj W. W., Robidoux N., Tadeusiewicz R.

Machine Graphics and Vision

2009

Vol. 18, No. 2

143-154

The classification of the various image features or visual objects can be carried out by the consistency-driven pairwise comparisons method based on their relative importance. A key issue in the proposed approach is a weight-based synthesis for combining various image features. When compared with the traditional experience-based linear assignment method, the proposed approach is more effective and easy to communicate.