Publication | Open Access
Comparison of 2D and 3D image-based aggregate morphological indices
84
Citations
15
References
2011
Year
EngineeringGeomorphologySpherical Harmonic FunctionsStatistical Shape AnalysisShape AnalysisGeological ModelingImage AnalysisMathematical MorphologyData ScienceAggregate ShapePattern RecognitionGeometry ProcessingGeometric ModelingMachine VisionGeographyMorphologyGeologyMedical Image ComputingMorphological AnalysisComputer VisionNatural SciencesCivil EngineeringGeomechanicsShape Modeling
Significant progress has been made over the last two decades in the characterisation of aggregate shape using automated image analysis and processing methods. Aggregate shape characteristics have been quantified using three distinct shape parameters, namely the aggregate form, angularity and surface texture. Several mathematical procedures have been developed to quantify these parameters. For practical reasons, most of these procedures were limited to two-dimensional (2D) and utilised 2D aggregate images. This paper investigates the ability of some of the most widely used 2D aggregate form and angularity indices to describe the shape of five different types of aggregates (natural gravel, basalt, granite, diabase and slate). In addition, it provides a comparison between 2D and three-dimensional (3D) aggregate shape indices developed based on fitting the 3D aggregate shape using spherical harmonic functions.
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