Título:
CS-TRD : A cross sections tree ring detection method.
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Autor:
Marichal, Henry
Passarella, Diego
Randall, Gregory
Passarella, Diego
Randall, Gregory
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Tipo de documento:
Preprint
Editor:
Palabras clave:
Image edge detection
Dendrochronology
Tree ring detection
Dendrochronology
Tree ring detection
Descriptores:
Año de publicación:
2024
Contenido:
Resumen:
This work describes a Tree Ring Detection method for complete Cross-Sections of Trees (CSTRD) 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 (σ), 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 of 97% in the Kennel dataset (of Abies alba) without specialized hardware requirements.
Descripción:
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EN:
TRACE 2024 - Tree Rings in Archaeology, Climatology and Ecology, annual meeting and international conference of the Association for Tree-Ring Research (ATR), Brasov, Romania, 3-8 jun. 2024, pp. 1-28.
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Citación:
Marichal, H., Passarella, D. y Randall, G. CS-TRD : A cross sections tree ring detection method [Preprint]. Publicado en: TRACE 2024 - Tree Rings in Archaeology, Climatology and Ecology, annual meeting and international conference of the Association for Tree-Ring Research (ATR), Brasov, Romania, 3-8 jun. 2024, pp. 1-28.
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Cobertura geográfica:
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imagenes
Licencia:
Licencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| MPR24.pdf | Preprint | 13.86 MB | Adobe PDF |