Abstract
This paper contains development of methods and algorithms of reduction for image recognition of mineral spices. It is known according to the practice of analyzing graphic pictures that for the majority of the digital images of the real world their size linear decreasing to a certain threshold does not lead to loss of the analyzed information. The main objective of this approach - define a threshold reduction of digital images. Some realizations of this algorithm are presented by defining criterion quantifying the loss of informative of modified image based. Few examples concerning with reduction in the solving of mineral species recognition problems are described and discussed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Harvey, B., Tracy, R.J.: Petrology: Igneous, Sedimentary, and Metamorphic, 2nd edn. W.H. Freeman, New York (1995)
Baklanova, O.E.: Development of algorithms for image recognition needed to assess the quality of the mineral species in the mining industry. In: Abstracts of International Conference Mathematical and Informational Technologies, MIT 2013, Vrnjacka Banja and Budva, September 5-September 14, pp. 63–64 (2013)
Baklanova, O.E., Uzdenbaev, Z.S.: Development of methodology for analysis of mineral rocks in the mining industry. In: Joint Issue of the Bulletin of the East Kazakhstan State Technical University and Computer Technology of Institute of Computational Technologies, Siberian Branch of the Russian Academy of Sciences, Part 1, pp. 60–66 (September 2013)
Clarke, A.R., Eberhardt, C.N.: Microscopy Techniques for Materials, 459 p. Science Woodhead Publishing, CRC Press (2002)
Panteleev, C., Egorova, O., Klykova, E.: Computer microscopy. Technosphere, 304 p. (2005)
Farndon, J.: The practical encyclopedia of rocks and minerals. How to Find, Identify, Collect and Maintain the World’s best Specimens, with over 1000 Photographs and Artworks. Lorenz Books, London (2006)
Chris, P.: Rocks and Minerals. In: Smithsonian Handbooks. Dorling Kindersley, New York (2002)
Shaffer, P.R., Herbert, S.Z., Raymond, P.: Rocks, Gems and Minerals, rev. edn. St. Martin’s Press, New York (2001)
Privalov, O.O., Butenko, L.N.: Algorithm of automatic reduction of digital images of bi-omedical preparations for performance systems auto automated microscopy. In: Modern Science Intensive Technologies: Scientific - Theoretical. Magazine, Moscow, vol. 10, pp. 80–82 (2007)
How to: Use Interpolation Mode to Control Image Quality During Scaling, http://msdn.microsoft.com/ru-ru/library/k0fsyd4e(v=vs.110).aspx
Interpolation Mode Enumeration, http://msdn.microsoft.com/ru-ru/library/system.drawing.drawing2d.interpolationmode(v=vs.110).aspx
Kim, C.-H., Seong, S.-M., Lee, J.-A., Kim, L.-S.: Winscale: An Image-Scaling Algorithm Using an Area Pixel Model. IEEE Transaction on Circuits and Systems for Video Technology 13(6), 549–553 (2003)
Gonsalez, R.C., Woods, R.E.: Digital image processing, 3rd edn., 976 p. Pearson Education (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Baklanova, O.E., Shvets, O.Y. (2014). Development of Methods and Algorithms of Reduction for Image Recognition to Assess the Quality of the Mineral Species in the Mining Industry. In: Chmielewski, L.J., Kozera, R., Shin, BS., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham. https://doi.org/10.1007/978-3-319-11331-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-11331-9_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11330-2
Online ISBN: 978-3-319-11331-9
eBook Packages: Computer ScienceComputer Science (R0)