X-Ray Tomography Crystal Characterization: Automatic 3D Segmentation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Microscopy and Microanalysis Année : 2023

X-Ray Tomography Crystal Characterization: Automatic 3D Segmentation

Résumé

Abstract Understanding the structural parameters of crystals during crystal growth is essential for the pharmaceutical and chemical industries. This study proposes a new method for 3D images of crystals obtained with micro X-ray computed tomography. This method aims to improve the crystal segmentation compared to the watershed methods. It is based on plane recognition at the surface of the crystals. The obtained segmentation is evaluated on a synthetic image and by considering the recognized particle number and convexity. The algorithm applied to three samples (potassium alum, chromium alum, and copper sulfate) reduced oversegmentation by 87% compared to watershed based on ultimate erosion while keeping the convexity of the recognized particle.

Dates et versions

hal-04055847 , version 1 (03-04-2023)

Identifiants

Citer

Gautier Hypolite, Jérôme Vicente, Philippe Moulin. X-Ray Tomography Crystal Characterization: Automatic 3D Segmentation. Microscopy and Microanalysis, 2023, 232, pp.119673. ⟨10.1093/micmic/ozad019⟩. ⟨hal-04055847⟩
14 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More