Identification of Primary Shape Descriptors on 3D Scanned Particles

Ludmány, Balázs; Domokos, G.

doi:10.3311/ppee.12313

Cited by 7 publications

(6 citation statements)

References 24 publications

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“…As such, more comprehensive datasets on grain size, shape, and composition, and their evolution through space (e.g., Cosgrove et al, 2019) are deeply needed. Novel methods or approaches for automatic grain characterization (e.g., Domokos et al, 2010;Ludmány and Domokos, 2018) might improve the comparison among datasets.…”

Section: Summary and Future Perspectives Environmental Signalsmentioning

confidence: 99%

Times Associated With Source-to-Sink Propagation of Environmental Signals During Landscape Transience

et al. 2021

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Sediment archives in the terrestrial and marine realm are regularly analyzed to infer changes in climate, tectonic, or anthropogenic boundary conditions of the past. However, contradictory observations have been made regarding whether short period events are faithfully preserved in stratigraphic archives; for instance, in marine sediments offshore large river systems. On the one hand, short period events are hypothesized to be non-detectable in the signature of terrestrially derived sediments due to buffering during sediment transport along large river systems. On the other hand, several studies have detected signals of short period events in marine records offshore large river systems. We propose that this apparent discrepancy is related to the lack of a differentiation between different types of signals and the lack of distinction between river response times and signal propagation times. In this review, we (1) expand the definition of the term ‘signal’ and group signals in sub-categories related to hydraulic grain size characteristics, (2) clarify the different types of ‘times’ and suggest a precise and consistent terminology for future use, and (3) compile and discuss factors influencing the times of signal transfer along sediment routing systems and how those times vary with hydraulic grain size characteristics. Unraveling different types of signals and distinctive time periods related to signal propagation addresses the discrepancies mentioned above and allows a more comprehensive exploration of event preservation in stratigraphy – a prerequisite for reliable environmental reconstructions from terrestrially derived sedimentary records.

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Section: Summary and Future Perspectives Environmental Signalsmentioning

confidence: 99%

Times Associated With Source-to-Sink Propagation of Environmental Signals During Landscape Transience

et al. 2021

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“…Although there exist approaches to analyze a 3D scanned geometry (Hayakawa and Oguchi, 2005;Deiros Quintanilla et al, 2019), they are unable to extract the number of stable and unstable equilibrium points. Our software is based on the algorithm of Ludmány and Domokos (2018) and available in Ludmány (2020b). It aims to automatically measure traditional three-dimensional shape properties and the number of equilibrium points.…”

Section: Softwarementioning

confidence: 99%

“…Secondly, we combine the technique with our algorithm to analyze a point cloud captured from the object and computationally determine its inherently threedimensional shape properties. Our method is based on a portable scanner Structure Sensor Mark I, and software built on a recently published algorithm (Ludmány and Domokos, 2018) to analyze the point cloud. We utilize the fact that the algorithm works with the convex envelope of the point cloud and a polygonal approximation.…”

Section: Introductionmentioning

confidence: 99%

Fully spherical 3D datasets on sedimentary particles: Fast measurement and evaluation

Fehér

Havasi-Tóth

Ludmány

2023

CEuGeol

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Recently it became increasingly evident that the statistical distributions of size and shape descriptors of sedimentary particles reveal crucial information on their evolution and may even carry the fingerprints of their provenance as fragments. However, to unlock this trove of information, measurement of traditional geophysical shape descriptors (mostly detectable on 2D projections) is not sufficient; fully spherical 3D imaging and mathematical algorithms suitable to extract new types of inherently 3D shape descriptors are necessary. Available 3D imaging technologies force users to choose either speed or full sphericity. Only partial morphological information can be extracted in the absence of the latter (e.g., LIDAR imaging). In the case of fully spherical imaging, speed was proved to be prohibitive for obtaining meaningful statistical samples, and inherently 3D shape descriptors were not extracted. Here we present a new method by complementing a commercial, portable 3D scanner with simple hardware to quickly obtain fully spherical 3D datasets from large collections of sedimentary particles. We also present software for the automated extraction of 3D shapes and automated measurement of inherently 3D-shape properties. This technique allows for examining large samples without the need for transportation or storage of the samples, and it may also facilitate the collaboration of geographically distant research groups. We validated our software on a large sample of pebbles by comparing previously hand-measured parameters with the results of automated shape analysis. We also tested our hardware and software tools on a large pebble sample in Kawakawa Bay, New Zealand.

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“…While the piecewise linear and the polyhedral problems are mathematically closely related, the applications driving these two models are somewhat different. While parallel distance functions can be efficient models in image processing and serve as good approximations in local cartography [10], radial distance functions are the only option in case of particle shape models in geomorphology and planetology [3,4,9,14]. Also, for global cartography, spherical geometry has to be taken into account.…”

Section: Introductionmentioning

confidence: 99%

“…While the mathematical properties of Morse-Smale complexes associated with a smooth mechanical distance function have been investigated in detail [5,8], so far there has been little experimental data to test this theory. The main obstacle in obtaining field data is the identification of Morse-Smale complexes on scanned images of particles [14]. These scans can be regarded as compact, polyhedral surfaces which we associate with the radial (mechanical) distance function.…”

Section: Introductionmentioning

confidence: 99%

Morse-Smale complexes on convex polyhedra

Ludmány¹,

Lángi²,

Domokos³

2021

Preprint

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Motivated by applications in geomorphology, the aim of this paper is to extend Morse-Smale theory from smooth functions to the radial distance function (measured from an internal point), defining a convex polyhedron in 3dimensional Euclidean space. The resulting polyhedral Morse-Smale complex may be regarded, on one hand, as a generalization of the Morse-Smale complex of the smooth radial distance function defining a smooth, convex body, on the other hand, it could be also regarded as a generalization of the Morse-Smale complex of the piecewise linear parallel distance function (measured from a plane), defining a polyhedral surface. Beyond similarities, our paper also highlights the marked differences between these three problems and it also includes the design, implementation and testing of an explicit algorithm computing the Morse-Smale complex on a convex polyhedron.

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Identification of Primary Shape Descriptors on 3D Scanned Particles

Cited by 7 publications

References 24 publications

Times Associated With Source-to-Sink Propagation of Environmental Signals During Landscape Transience

Times Associated With Source-to-Sink Propagation of Environmental Signals During Landscape Transience

Fully spherical 3D datasets on sedimentary particles: Fast measurement and evaluation

Morse-Smale complexes on convex polyhedra

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