Machine Vision and Applications

, Volume 16, Issue 5, pp 282–288 | Cite as

A mathematical morphology approach to image based 3D particle shape analysis

  • J. R. J. Lee
  • M. L. Smith
  • L. N. Smith
  • P. S. Midha


Angularity is a critically important property in terms of the performance of natural particulate materials. It is also one of the most difficult to measure objectively using traditional methods. Here we present an innovative and efficient approach to the determination of particle angularity using image analysis. The direct use of three-dimensional data offers a more robust solution than the two-dimensional methods proposed previously. The algorithm is based on the application of mathematical morphological techniques to range imagery, and effectively simulates the natural wear processes by which rock particles become rounded. The analysis of simulated volume loss is used to provide a valuable measure of angularity that is geometrically commensurate with the traditional definitions. Experimental data obtained using real particle samples are presented and results correlated with existing methods in order to demonstrate the validity of the new approach. The implementation of technologies such as these has the potential to offer significant process optimisation and environmental benefits to the producers of aggregates and their composites. The technique is theoretically extendable to the quantification of surface texture.


3D particle analysis 3D shape analysis Mathematical morphology 


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  1. 1.
    Mora, C.F., Kwan, A.K.H.: Sphericity, shape factor, and convexity measurement of coarse aggregate for concrete using digital image processing. Cement Concrete Res. 30, 351–358 (2000)CrossRefGoogle Scholar
  2. 2.
    Wilson, J.D., Klotz, L.D., Nagaraj, C.: Automated measurement of aggregate indices of shape. Part. Sci. Technol. 15, 13–35 (1997)CrossRefGoogle Scholar
  3. 3.
    Masad, E., Olcott, D., White, T., Tashman, L. Correlation of fine aggregate imaging shape indices with asphalt mixture performance. Transp. Res. Rec. 1757, 148–157 (2001)CrossRefGoogle Scholar
  4. 4.
    Masad, E., Button, J.: Unified imaging approach for measuring aggregate angularity and texture. Comput. Aid. Civil Infrastruct. Eng. 15, 273–280 (2000)CrossRefGoogle Scholar
  5. 5.
    Leavers, V.F.: An active angularity factor for the characterization of abrasive particles. Wear 239, 102–110 (2000)CrossRefGoogle Scholar
  6. 6.
    Vallejo, L.E.: Fractal analysis of granular materials. Géotechnique 45(1), 159–163 (1995)CrossRefGoogle Scholar
  7. 7.
    Pons, M.N., Vivier, H., Belaroui, K., Bernard-Michel, B., Cordier, F., Oulhana, D., Dodds, J.A.: Particle morphology: from visualization to measurement. Powder Technol. 103, 44–57 (1999)CrossRefGoogle Scholar
  8. 8.
    Bérubé, D., Jébrak, M.: High precision boundary fractal analysis for shape characterization. Comput. Geosci. 25, 1059–1071 (1999)CrossRefGoogle Scholar
  9. 9.
    Moore, C.A., Donaldson, C.F.: Quantifying soil microstructure using fractals. Géotechnique 45(1), 105–116 (1995)Google Scholar
  10. 10.
    Sternberg, S.R.: Grayscale morphology. CVGIP 35, 333–355 (1986)Google Scholar
  11. 11.
    Koskinen, L., Astola, J., Neuvo, Y.: Soft morphological filters. Proc. SPIE 1568, 262–270 (1991)CrossRefGoogle Scholar
  12. 12.
    Serra, J.: Image Analysis and Mathematical Morphology. Academic, London (1982)Google Scholar
  13. 13.
    Kuosmanen, P., Astola, J.: Soft morphological filtering. J. Math. Imaging Vis. 5, 231–262 (1995)CrossRefzbMATHGoogle Scholar
  14. 14.
    Bribiesca, E.: Measuring 2-D shape compactness using the contact perimeter. Comput. Math. Appl. 33(11), 1–9 (1997)CrossRefMathSciNetzbMATHGoogle Scholar
  15. 15.
    Bribiesca, E.: A measure of compactness for 3D shapes. Comput. Math. Appl. 40, 1275–1284 (2000)CrossRefMathSciNetzbMATHGoogle Scholar
  16. 16.
    Powers, M.C.: A new roundness scale for sedimentary particles. J. Sediment. Petrol. 23, 117–119 (1953)Google Scholar
  17. 17.
    Wadell, H.: Volume, shape, and roundness of quartz particles. J. Geol. 43, 250–280 (1935)CrossRefGoogle Scholar
  18. 18.
    Lanaro, F., Tolppanen, P.: 3D characterization of coarse aggregates. Eng. Geol. 65, 17–30 (2002)CrossRefGoogle Scholar
  19. 19.
    Maerz, N.H.: Technical and computational aspects of the measurement of aggregate shape by digital image analysis. J. Comput. Civil Eng. 18, 10–18 (2004)CrossRefGoogle Scholar
  20. 20.
    MacLeod, N.: Geometric morphometrics and geological form-classification systems. Earth Sci. Rev. 59, 27–47 (2002)CrossRefGoogle Scholar
  21. 21.
    BS 812: 1975—Methods for Sampling and Testing of Mineral Aggregates and Fillers. British Standards Institution, London (1975)Google Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • J. R. J. Lee
    • 1
  • M. L. Smith
    • 1
  • L. N. Smith
    • 1
  • P. S. Midha
    • 1
  1. 1.Machine Vision Laboratory, Faculty of Computing, Engineering and Mathematical SciencesUniversity of the West of EnglandBristolUK

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