Measurement Techniques

, Volume 51, Issue 2, pp 146–151 | Cite as

Metrological aspects of image analysis

  • V. V. Fomin
  • A. P. Mikhailovich
  • A. S. Popov
  • N. F. Nizametdinov
  • Yu. V. Shalaumova


A universal approach to the detection of drawbacks in techniques used to perform measurements based on the use of systems for automatic image analysis is considered. A regression model that makes it possible to estimate the contribution of errors characterizing the photography conditions and camera setting adjustment is constructed. The accuracy indicators (correctness and precision indicators) are estimated in accordance with an existing standard.

Key words

automated image analysis accuracy indicators 


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  1. 1.
    V. I. Grokhovskii, Digital Microscopy. Proc. of a School Seminar [in Russian], GOU VPO UGTU-UPI, Ekaterinburg (2001), p. 18.Google Scholar
  2. 2.
    I. N. Veselov et al., Vestnik UGTU-UPI, No. 10, 41 (2005).Google Scholar
  3. 3.
    K. Marias et al., Europ. J. Radiation, 52, 276 (2004).CrossRefGoogle Scholar
  4. 4.
    W. Chen et al., Computer Methods and Programs in Biomedicine, 79, 58 (2005).CrossRefGoogle Scholar
  5. 5.
    J.-F. Mangin et al., Artificial Intelligence in Medicine, 30, 177 (2004).CrossRefGoogle Scholar
  6. 6.
    L. H. Stein et al., Acuaculture, 261, 695 (2006).Google Scholar
  7. 7.
    J. Scott et al., Remote Sensing of the Environment, 88, 195 (2003).CrossRefGoogle Scholar
  8. 8.
    L. Dragut and T. Blaschhke, Geomorphology, 81, 330 (2006).CrossRefADSGoogle Scholar
  9. 9.
    M. E. Jakubauskas, D. R. Legates, and J. H. Kastens, Computers and Electronics in Agriculture, 37, 127 (2002).CrossRefGoogle Scholar
  10. 10.
    BS 3406-4:1993, Method for Determination of Particle Size Distribution: Part 4: Guide to Microscope and Image Analysis Method.Google Scholar
  11. 11.
    ASTM E 1245-03, Standard Practice for Determining the Inclusion of Second-Phase Constituent Content of Metal by Automatic Image Analysis.Google Scholar
  12. 12.
    ISO 13322-1:2000, Static Image Analysis Methods.Google Scholar
  13. 13.
    GOST R 8.563-96, GSI, Techniques for Performing Measurements.Google Scholar
  14. 14.
    B. S. Ligachev, Zakonodat. Prikl. Metrol., No. 2, 11 (1997).Google Scholar
  15. 15.
    E. I. Sychaev, Zakonodat. Prikl. Metrol., No. 4, 45 (1997).Google Scholar
  16. 16.
    GOST R ISO 5725-2002, Accuracy (Correctness and Precision) of Methods and Measurement Results: Parts 1–6.Google Scholar
  17. 17.
    Yu. P. Adler, E. V. Markova, and Yu. V. Granovskii, Experiment Design in the Search for Optimal Conditions [in Russian], Nauka, Moscow (1976).Google Scholar
  18. 18.
    E. Muller and H. R. Stierlin, Sanasilva. Tree Crown Photos, Swiss Federal Institute for Forest, Snow and Landscape Research, Birmensdorf (Switzerland) (1990).Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2008

Authors and Affiliations

  • V. V. Fomin
    • 1
  • A. P. Mikhailovich
    • 3
  • A. S. Popov
    • 2
  • N. F. Nizametdinov
    • 2
  • Yu. V. Shalaumova
    • 2
  1. 1.SIAMS CompanyEkaterinburgRussia
  2. 2.Laboratory of GIS TechnologiesUral State Forestry InstituteEkaterinburgRussia
  3. 3.Ural State Technical InstituteEkaterinburgRussia

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