A stochastic 3D model based on random graphs to characterize the morphology of compact aggregates using image analysis - Mines Saint-Étienne
Communication Dans Un Congrès Année : 2024

A stochastic 3D model based on random graphs to characterize the morphology of compact aggregates using image analysis

Résumé

Morphological characterization of aggregates using image analysis is a key problem in many research areas. In particular, the estimation of 3D characteristics from projected 2D images is both complex and necessary. In this paper, a stochastic geometric 3D model called SWARM (Stochastic Wandering particle AgglomeRation Model) is developed based on hard sphere packing and random graphs. A method to adjust the model parameters by image analysis using morphological skeletons is presented and doubly validated on synthetic and 3D printed aggregates. The results obtained show relative errors of the order of 1% in most cases and 4% in the worst case, making it a very efficient model compared to similar models. Finally, limitations are discussed and possible improvements are suggested.
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vendredi 10 janvier 2025
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Dates et versions

emse-04639028 , version 1 (10-07-2024)

Identifiants

Citer

Léo Théodon, Carole Coufort-Saudejaud, Johan Debayle. A stochastic 3D model based on random graphs to characterize the morphology of compact aggregates using image analysis. ISIVC 2024, Hassan II University of Casablanca; FST Mohammedia, Hassan II University of Casablanc; National Centre for Scientific and Technical Research (CNRST); IMT Atlantique; Mohammed V University of Rabat; Sup’Com, Tunis, Tunisie; ENSA, Marrakech, Maroc; ENSA, El Jadida, Maroc; INSA, Université Claude Bernard Lyon 1, France; IDP, Universityé d'Orleans, France, May 2024, Marrakech, Morocco. pp.10577874, ⟨10.1109/ISIVC61350.2024.10577874⟩. ⟨emse-04639028⟩
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