CS-TRD: a Cross-Section Tree Ring Detection Method

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 relies on edge detection, and its parameters are set to default values and can be adjusted as needed. The only required input is the location of the biological center of the tree, the pith, which can be marked manually or using an automatic detection algorithm. CS-TRD achieves an F-Score of 91% in the UruDendro dataset (of Pinus taeda) and 97% in the Kennel dataset (of Abies alba) without specialized hardware requirements.

Authors

Publication Details

Journal
Image Processing On Line
Published
2025-12-27
DOI
https://doi.org/10.5201/ipol.2025.485
Citations
2
Primary Topic
Wood and Agarwood Research
Type
article
Field-Weighted Citation Impact
1.87
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article

CS-TRD: a Cross-Section Tree Ring Detection Method

Diego Passarella, Henry Marichal, Gregory Randall
2 citations
Image Processing On Line
Wood and Agarwood Research
1.87
article

CS-TRD: a Cross-Section Tree Ring Detection Method

Diego Passarella, Henry Marichal, Gregory Randall
article en
2 citations

Abstract

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 relies on edge detection, and its parameters are set to default values and can be adjusted as needed. The only required input is the location of the biological center of the tree, the pith, which can be marked manually or using an automatic detection algorithm. CS-TRD achieves an F-Score of 91% in the UruDendro dataset (of Pinus taeda) and 97% in the Kennel dataset (of Abies alba) without specialized hardware requirements.

Image Processing On LineVol. 15
Life in Land
Openalex Percentile: Top 13%
Wood and Agarwood Research
1.87
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