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

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Języki publikacji
EN
Abstrakty
EN
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.
Wydawca
Rocznik
Strony
156--176
Opis fizyczny
Bibliogr. 37 poz., fot., rys.
Twórcy
autor
  • Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba R3T 5V6 Canada
autor
  • Institute of Mathematics, The University of Warsaw, Banacha 2, 02-097 Warsaw, Poland
autor
  • Faculty of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland
Bibliografia
  • [1] Armstrong, H., Brasier, M.: Microfossils, 2nd Ed., Blackwell Publishing, Malden, MA, U.S.A., 2005.
  • [2] Bazan, J.: Hierarchical Classifiers for Complex Spatio-temporal Concepts, in: Transactions on Rough Sets IX: Journal Subline (J. F. Peters, A. Skowron, H. Rybinski, Eds.), vol. 5390 of Lecture Notes in Computer Science, Springer, Heidelberg, 2008, 474-750.
  • [3] Di Concilio, A.: Proximity: A powerful tool in extension theory, functions spaces, hyperspaces, boolean algebras and point-free geometry, in: Beyond Topology, AMS Contemporary Mathematics 486 (F. Mynard, E. Pearl, Eds.), Amer. Math. Soc., 2009, 89-114.
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  • [5] Di Concilio, A., Naimpally, S.: Proximal convergence, Monatsh. Math., 103, 2006, 93-102.
  • [6] Efremovic, V.: The geometry of proximity I, Mat. Sb., 31, 1951, 189-200 (in Russian), MR 14, 1106.
  • [7] Ellison, S.: Microfossils as environment indicators in marine shales, J Sedimentary Petrology, 21(4), 1951, 214-225.
  • [8] Jones, D.: Displacement of microfossils, J Sedimentary Petrology, 28(4), 1958,453-467.
  • [9] Lesniewski, S.: Grundzuge eines neuen Systems der Grundlagen der Mathematik, Fundamenta Mathemati- cae, 14, 1929, 1-81.
  • [10] Mitchell, M.: Analogy-Making as Perception, MIT Press, Cambridge, MA, U.S.A., 1993.
  • [11] Naimpally, S.: Proximity Spaces, Cambridge University Press, Cambridge,UK, 1970, X+128 pp., ISBN 978-0-521-09183-1.
  • [12] Naimpally, S., Peters, J.: Topology with Applications. Topological Spaces via Near and Far, World Scientific, Singapore, 2013, in press.
  • [13] Nguyen, H. S.: Approximate Boolean reasoning: Foundations and Applications in Data Mining, in: Transactions on Rough Sets V: Journal Subline (J. F. Peters, A. Skowron, Eds.), vol. 4100 of Lecture Notes in Computer Science, Springer, Heidelberg, 2006, 344-523.
  • [14] Pawlak, Z.: Rough sets, International J. Comp. Inform. Science, 11, 1982, 341-356.
  • [15] Pawlak, Z., Skowron, A.: Rough sets and Boolean reasoning, Information Sciences, 177, 2007, 41-73.
  • [16] Pawlak, Z., Skowron, A.: Rough sets: Some extensions, Information Sciences, 177, 2007, 28-40.
  • [17] Pawlak, Z., Skowron, A.: Rudiments of rough sets, Information Sciences, 177, 2007, 3-27.
  • [18] Pedrycz, W., Skowron, A., Kreinovich, V., Eds.: Handbook of Granular Computing, Wiley & Sons, New York, USA, 2008.
  • [19] Peters, J.: Local near sets. Pattern discovery in proximity spaces, Math. in Comp. Sci., 2013, to appear.
  • [20] Peters, J., Naimpally, S.: Applications of near sets, Amer. Math. Soc. Notices, 59(4), 2012, 536-542.
  • [21] Peters, J., Ramanna, S.: Pattern discovery with local near sets, Proc. Jornadas Chilenas de Computación 2012 workshop on pattern recognition (R. Alarcon, P. Barcelo, Eds.), The Chilean Computing Society, Valparaiso, 2012.
  • [22] Peters, J., Skowron, A., Stepaniuk, J.: Nearness of objects: Extension of approximation space model, Fundamenta Informaticae, 79(3-4), 2007, 497-512.
  • [23] Polkowski, L.: Approximate Reasoning by Parts. An Introduction to Rough Mereology, vol. 20 of Intelligent Systems Reference Library, Springer, Heidelberg, 2011.
  • [24] Polkowski, L., Skowron, A.: Rough Mereology: A New Paradigm for Approximate Reasoning, International Journal of Approximate Reasoning, 15(4), 1996, 333-365.
  • [25] Polkowski, L., Skowron, A.: Towards Adaptive Calculus of Granules, Computing with Words in Information/Intelligent Systems (L. A. Zadeh, J. Kacprzyk, Eds.), Physica-Verlag, Heidelberg, 1999.
  • [26] Skowron, A.: Rough sets in KDD - plenary talk, in: 16-th World Computer Congress (IFIP’2000): Proceedings of Conference on Intelligent Information Processing (IIP’2000) (Z. Shi, B. Faltings, M. Musen, Eds.), Publishing House of Electronic Industry, Beijing, 2000, 1-14.
  • [27] Skowron, A., Stepaniuk, J.: Tolerance Approximation Spaces, Fundamenta Informaticae, 27(2-3), 1996, 245-253.
  • [28] Skowron, A., Stepaniuk, J.: Approximation of functions: Toward rough granule calculus, in: Rough Sets and Knowledge Technology, LNAI6954 (J. Yao, S. Ramanna, G. Wang, Z. Suraj, Eds.), Springer, 2012, 712-721.
  • [29] Smirnov, J.: On proximity spaces, Mat. Sb., 31(73), 1952, 543-574 (in Russian).
  • [30] Solomon, C., Breckon, T.: Fundamentals of Digital Image Processing, Wiley-Blackwell Publishing, London, UK, 2011.
  • [31] Stepaniuk, J.: Rough-Granular Computing in Knowledge Discovery and Data Mining, Springer, Berlin Heidelberg, 2008, ISBN 978-3-540-70801-8.
  • [32] Tversky, A.: Features of similarity, Psychological Review, 84, 1977, 327352.
  • [33] Tversky, A.: Preference, Belief, and Similarity (edited by Eldar Shafir), MIT Press, Massachusetts Institute of Technology, 2004.
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  • [35] Zadeh, L. A.: Fuzzy sets and information granularity, in: Advances in Fuzzy Set Theory and Applications (M. Gupta, R. Ragade, R. Yager, Eds.), North-Holland, Amsterdam, 1979, 3-18.
  • [36] Zadeh, L. A.: From computing with numbers to computing with words - from manipulation of measurements to manipulation of perceptions, IEEE Transactions on Circuits and Systems, 45, 1999, 105-119.
  • [37] Zadeh, L. A.: A new direction in AI-toward a computational theory of perceptions, AI Magazine, 22(1), 2001, 73-84.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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