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Computer Science > Computer Vision and Pattern Recognition

Title: CS-TRD: a Cross Sections Tree Ring Detection method

Abstract: This work describes a Tree Ring Detection method for complete Cross-Sections of trees (CS-TRD). The method is based on the detection, processing, and connection of edges corresponding to the tree's growth rings. The method depends on the parameters for the Canny Devernay edge detector ($\sigma$ and two thresholds), a resize factor, the number of rays, and the pith location. The first five parameters are fixed by default. The pith location can be marked manually or using an automatic pith detection algorithm. Besides the pith localization, the CS-TRD method is fully automated and achieves an F-Score of 89\% in the UruDendro dataset (of Pinus Taeda) with a mean execution time of 17 seconds and of 97\% in the Kennel dataset (of Abies Alba) with an average execution time 11 seconds.
Comments: presented to Ipol
Subjects: Computer Vision and Pattern Recognition (cs.CV); Populations and Evolution (q-bio.PE)
Cite as: arXiv:2305.10809 [cs.CV]
  (or arXiv:2305.10809v1 [cs.CV] for this version)

Submission history

From: Gregory Randall [view email]
[v1] Thu, 18 May 2023 08:43:57 GMT (41248kb,D)

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