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Application of database technology to analysis of rock structure images

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Języki publikacji
EN
Abstrakty
EN
The aim of this paper is to present a possibility to use information technology in the form of databases for processing and analyzing large image sets based on methods of image analysis and mathematical morphology. Up to now the use of databases in the image analysis process has been reduced to storing large amounts of data in the form of images. However, all transformations and analyses of such sets are made on user’s computers. This requires a large data set (images) to be sent by network each time, and also it may possess the problems resulting from managing such large amounts of analyzed photographs on a computer. The proposed approach completely eliminates these problems by moving all transformations of image analysis to a database platform. For this purpose a set of routines realizing transformations of the image analysis and mathematical morphology was developed. The proposed approach allows the unification of the image processing and analysis area and advanced statistical analyses of obtained parameters describing geometrical sizes of objects on photographs. The proposed methodology was illustrated by practical realization of two measurement types for a simple structure of copper concentrate and more complicated, from the point of view of image analysis, structures such as dolomites from Redziny and Laskowa Gora and sandstones from Tumlin and Wisniowka.
Rocznik
Strony
563--573
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
  • AGH University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection, Department of Geoinformatics and Applied Computer Science, al. Mickiewicza 30, 30-059 Cracow, Poland
autor
  • AGH University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection, Department of Geoinformatics and Applied Computer Science, al. Mickiewicza 30, 30-059 Cracow, Poland,
  • AGH University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection, Department of Geoinformatics and Applied Computer Science, al. Mickiewicza 30, 30-059 Cracow, Poland
Bibliografia
  • 1. BATINI C., CERI S., NAVATHE S.B., 1992, Conceptual database design: an Entity-relationship approach,. Redwood City: Benjamin/Cummings.
  • 2. BODZIONY J., 1965, On Certain Indices Characterizing the Geometric Structure of Rocks, Bulletin de l’Academie Polonaise des Sciences, 8, 9.
  • 3. BODZIONY J., KRAJ W., PINDEL Z., RATAJCZAK T., WILCZYŃSKI J., 1979, Analiza stereo-logiczna zespołu minerałów miedzionośnych białego spągowca, Archiwum Górnictwa, 24.
  • 4. BODZIONY J., MŁYNARCZUK M., RATAJCZAK T., 1993, Identification of trans-and intercrystalline image of the fracture surfaces of rock specimens, Acta Stereol, 12, 2.
  • 5. CHUCHRO M., PIÓRKOWSKI A., 2010, Methods and tools for data mining of intensity variability inlet to municipal wastewater treatment plant, Studia Informatica, 31, no 2B, 347–358.
  • 6. DRZYMALA J., 2009, Podstawy mineralurgii. Oficyna Wyd. Politechniki Wrocławskiej.
  • 7. FANDRICH R., et al., 2007, Modern SEM-based mineral liberation analysis. International Journal of Mineral Processing, 84, 310–320.
  • 8. GONZALEZ RC., WINTZ P., 1987, Digital Image Processing, Addison Wesley.
  • 9. GOODALL W. R., SCALES P. J., BUTCHER A. R., 2005, The use of QEMSCAN and diagnostic leaching in the characterisation of visible gold in complex ores, Minerals Engineering, 18, 877–886.
  • 10. KRAJ W., RATAJCZAK T., 1989, Zastosowanie funkcji kowariancji do scharakteryzowania struktury węgła dolnośląskiego, Archiwum Górnictwa, 34.
  • 11. KRAJ W., KRUSZYŃSKI M., 1981, Wyznaczanie orientacji przestrzennej nieciągłości w skale na przykładzie granitu strzegomskiego. Archiwum Górnictwa 26(3).
  • 12. LADNIAK M., PIORKOWSKI A., MŁYNARCZUK M., 2013a, Structure of systems for data exploration for raster images, Studia Informatica, vol. 34, no 2B (112), 7–20.
  • 13. LADNIAK M., PIORKOWSKI A., MŁYNARCZUK M., 2013b, The Data Exploration System for Image Processing Based on Server-Side Operations, Lecture Notes in Computer Sciences 8104, 156–164.
  • 14. MILLER P.R., REID A. F., ZUIDERWYK M. A., 1982, QEM* SEM image analysis in the determination of modal assays, mineral associations, and mineral liberation, Proceedings XIV International Mineral Processing Congress, 3.
  • 15. MLYNARCZUK M., 1999, Some Remarks on the Application of Image Analysis and Image Processing for the Description of the Geometrical Structures of Rock, Physicochemical Problems of Mineral Processing, 33, 107–116.
  • 16. MLYNARCZUK M., 2006, Możliwości wykorzystania metod analizy obrazu do opisu petrograficznego wybranych skał okruchowych, Gospodarka Surowcami Mineralnymi, 22, 3, 135–144.
  • 17. MLYNARCZUK M., 2008, Zastosowanie metod analizy obrazu i morfologii matematycznej do ilosciowego opisu ukształtowania powierzchni przelamow skalnych, Archives of mining Sciences, Monografie.
  • 18. OBARA B., 2007, Identification of transcrystalline microcracks observed in microscope images of dolomite structure using image analysis methods based on linear structuring element processing, Computers & Geosciences 33, 151–158.
  • 19. PIRRIE D., et al., 2004, Rapid quantitative mineral and phase analysis using automated scanning electron microscopy (QemSCAN), potential applications in forensic geosciences, Geological Society, 232, 123-136.
  • 20. PETRUK W., 1988a. Automatic image analysis for mineral beneficiation, Journal of Metals 40 (4), 29–31.
  • 21. PETRUK W., 1988b. Automatic image analysis to determine mineral behaviour during mineral beneficiation, Process Mineralogy VIII. In: Carson, D.J.T., Vassiliou, A.H. (Eds.). The Minerals, Metals & Materials Society, 347–357.
  • 22. PETRUK W., 1989, Short course on image analysis applied to mineral and earth sciences, Mineralogical Association of Canada, Ottawa.
  • 23. PETRUK W., WILSON J.M.D., LASTRA R., HEALY R.E., 1991. An image analysis and materials balancing procedure for evaluating ores and mill products to obtain optimum recoveries. Proceedings of 23rd Annual Meeting of the Canadian Mineral Processors, 1–16. (Section 19).
  • 24. RAMAKRISHNAN, R., GEHRKE, J., 2000, Database management systems, Osborne/McGraw-Hill.
  • 25. SERRA, J., 1982, Image Analysis and Mathematical Morphology, Academic Press, London.
  • 26. SERRA J., MŁYNARCZUK M., 2000: Morphological Merging of Multidimensional Data, Proceedings of STERMAT.
  • 27. TADEUSIEWICZ R., KOROHODA P., 1997, Komputerowa analiza i przetwarzanie obrazów, Wydawnictwo Fundacji Postępu Telekomunikacji.
  • 28. TASDEMIR A., 2008, Evaluation of grain size distribution of unbroken chromites, Minerals Engineering, 21 (10), 711–719.
  • 29. TASDEMIR A. OZDAG H. ONAL G., 2011, Image analysis of narrow size fractions obtained by sieve analysis - an evaluation by log-normal distribution and shape factors, Physicochem. Probl. Miner. Process. 46 (2011) 95-106
  • 30. ULLMAN J. D., 1985, Principles of database systems, Galgotia Publications.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2a8202bc-8ff9-4ec0-b570-00fe87447870
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