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

Authors:
J. Lee;L. Smith;N. Smith;S. Midha
Affiliations:
Machine Vision Laboratory, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, UK;Machine Vision Laboratory, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, UK;Machine Vision Laboratory, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, UK;Machine Vision Laboratory, Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, UK
Venue:
Machine Vision and Applications
Year:
2005

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Abstract

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.