The analysis of probabilistic properties of the partition metric

Authors

  • Е.А. Егорова Кафедра информатики Харьковский национальный университет радиоэлектроники, Ukraine
  • А.К. Фурсенко Кафедра высшей математики Харьковский университет воздушных сил, Ukraine
  • В.В. Шляхов Кафедра информатики Харьковский национальный университет радиоэлектроники, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2010.2645

Keywords:

metric, partitions, visual information interpretation

Abstract

The paper considers probabilistic properties of the partition metric what allows to operate not only hard segmented image but its nested partitions which provides additional abilities for visual information analysis and interpretation.

Author Biographies

Е.А. Егорова, Кафедра информатики Харьковский национальный университет радиоэлектроники

Кандидат технических наук, старший научный сотрудник

А.К. Фурсенко, Кафедра высшей математики Харьковский университет воздушных сил

Кандидат технических наук, доцент

В.В. Шляхов, Кафедра информатики Харьковский национальный университет радиоэлектроники

Кандидат технических наук, ведущий научный сотрудник

References

  1. A. Bargiela, W. Pedrycz. Granular computing: an introduction //The Kluwer International Series in Engineering and Computer Science. Boston, Kluwer Academic Publishers. – Vol. 717. –2002.. – 478 p.
  2. Y.Y. Yao. Perspectives of granular computing / // Proceedings of IEEE International Conference on Granular Computing.– Vol. 1. – 2005. – P. 85-90.
  3. P. Doherty, W. Lukaszewicz, A. Szalas. Information granules for intelligent knowledge structures // Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing / G. Wang, et al. (Eds.). – Lecture Notes in Artificial Intelligence. – Berlin Heidelberg: Spinger-Verlag.– Vol. 2639. – 2003.– P. 405-412.
  4. T.Y. Lin. Granular computing (Structures, representations, and applications) // Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing / G. Wang, et al. (Eds.). Lecture Notes in Artificial Intelligence. Berlin Heidelberg: SpingerVerlag.– Vol. 2639. – 2003. – P. 16-24.
  5. В.П.Машталир, В.В. Шляхов. Свойства мультиалгебраических систем в задачах компаративного распознавания / Кибернетика и системный анализ. – №6. – 2003.– С. 12-32.
  6. A.K. Jain, M.N. Murty, P.J. Flynn. Data clustering: a review // ACM Computing Surveys. Vol. 31, No. 3. –– 1999. – P. 264–323.
  7. E. Chavez, G. Navarro, R. Baeza-Yates, J. L. Marroquin. Searching in metric spaces // ACM Computing Surveys (CSUR). – Vol. 33, No. 3. – 2001. – P. 273-321.
  8. M. Meila. Comparing clusterings by the variation of information // Learning Theory and Kernel Machines. Lecture Notes in Computer Science. Berlin Heidelberg: SpringerVerlag.– Vol. 2777. –2003. – P. 173-187.
  9. G. Hjaltason, H. Samet. Index-driven similarity search in metric spaces // ACM Transactions on Database Systems (TODS).– Vol. 28, No. 4. – 2003. – P. 517-580.
  10. Y. Rubner, C. Tomasi, L.J.Guibas. The Earth Mover’s Distance as a Metric for Image Retrieval / // International Journal of Computer Vision. Springer, Netherlands. – Vol. 40, No 2. – 20003. – P. 99-121.
  11. R.O. Stehling, M.A. Nascimento, A.X. Falcao. MiCRoM: A metric to compare segmented images // VISUAL 2002 / S.-K. Chang, Z. Chen, S.-Y. Lee. (Eds.). Lecture Notes in Computer Science. Berlin Heidelberg: Springer-Verlag.– Vol. 2314. – 2002. – P. 12–23.
  12. V. Mashtalir, E. Mikhnova, V. Shlyakhov, E. Yegorova. Novel metric on partitions for image segmentation / // Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance. avss. – 2006. – P. 18.
  13. A partition metric for clustering features analysis / D. Kinoshenko, V. Mashtalir, V. Shlyakhov // International Journal “Information Theories and Applications”.– Vol. 14, No 3. – 2007. – P. 230-236.

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Published

2010-04-06

How to Cite

Егорова, Е., Фурсенко, А., & Шляхов, В. (2010). The analysis of probabilistic properties of the partition metric. Eastern-European Journal of Enterprise Technologies, 2(4(44), 10–15. https://doi.org/10.15587/1729-4061.2010.2645

Issue

Vol. 2 No. 4(44) (2010): Mathematics and cybernetics - fundamental and applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2014 Е.А. Егорова, А.К. Фурсенко, В.В. Шляхов

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