Papers › CS-TRD: a Cross Sections Tree Ring Detection method
CS-TRD: a Cross Sections Tree Ring Detection method
Henry Marichal, Diego Passarella, Gregory Randall
This work describes a Tree Ring Detection method for complete Cross-Sections of Trees (CS-TRD) that detects, processes and connects edges corresponding to the tree's growth rings. The method depends on the parameters for the Canny Devernay edge detector (sigma), a resize factor, the number of rays, and the pith location. The first five are fixed by default. The pith location can be marked manually or using an automatic pith detection algorithm. Besides the pith localization, CS-TRD is fully automated and achieves an F-Score of 89% in the UruDendro dataset (of Pinus taeda) and 97% in the Kennel dataset (of Abies alba) without specialized hardware requirements.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Boundary Detection | UruDendro | CS-TRD | Average Precision | 0.94 | #1 of 2 | Archive leaderboard | report |
| Boundary Detection | UruDendro | CS-TRD | Average Recall | 0.88 | #1 of 2 | Archive leaderboard | report |
| Boundary Detection | UruDendro | CS-TRD | F1-score | 0.91 | #1 of 2 | Archive leaderboard | report |
| Boundary Detection | UruDendro | CS-TRD | FScore | 0.91 | #1 of 2 | Archive leaderboard | report |
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