CVPEMay 18, 2023

CS-TRD: a Cross Sections Tree Ring Detection method

arXiv:2305.10809v24 citations
Originality Synthesis-oriented
AI Analysis

This addresses tree ring analysis for dendrochronology, but it is incremental as it builds on existing edge detection techniques.

The authors tackled the problem of detecting tree rings in cross-sections by developing CS-TRD, a method that automates edge detection and connection, achieving an F-Score of 89% on the UruDendro dataset and 97% on the Kennel dataset.

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 Implementations1 repo
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