Articles | Volume 14, issue 4
https://doi.org/10.5194/esurf-14-527-2026
https://doi.org/10.5194/esurf-14-527-2026
Research article
 | 
14 Jul 2026
Research article |  | 14 Jul 2026

ImageGrains 2.0: Improved precision and generalization for grain segmentation

David Mair, Guillaume Witz, Ariel Do Prado, Philippos Garefalakis, Amanda Wild, Fanny Ville, Bennet Schuster, Michael Horn, Jürgen Österle, Stefano C. Fabbri, Camille Litty, Stefan Achleitner, Sebastian Leistner, Clemens Hiller, and Fritz Schlunegger

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Short summary
This study introduces an updated image analysis framework for automatically identifying and measuring sediment grains in various types of images and scans. We employ a high-performing segmentation approach for a wide range of geoscientific data, using carefully curated ground truth data. The method achieves higher accuracy and more consistent measurements than existing approaches. The data and algorithm are openly available and provided in a user-friendly way.
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