TRAS: An Interactive Software for Tracing Tree Ring Cross Sections

2026-05-08

AI Summary

This study addresses the limitations of traditional tree-ring marking, which relies on manual annotation and suffers from being time-consuming, subjective, and difficult to scale. To overcome these challenges, the authors present TRAS, an open-source interactive software that integrates classical image processing (CS-TRD) with two deep learning models (DeepCS-TRD and INBD) to enable both automatic detection and efficient manual correction of tree rings. Evaluated on pine wood images, the method achieves an F-score of 81.0% in automatic ring detection, reduces manual correction effort to approximately 20%, and yields ring-width measurements highly consistent with those from CooRecorder (r > 0.99). TRAS thus significantly enhances the efficiency, accuracy, and reproducibility of dendrochronological analysis while supporting cross-platform deployment.

Abstract

Tree ring marking remains a key step in dendrometry and dendrochronology, but it is often performed manually, making the process time-consuming, subjective, and difficult to scale to large image datasets. We present the Tree Ring Analyzer Suite (TRAS), an open-source graphical software for automatic delineation, manual correction, and measurement of tree rings in wood cross-sectional images. TRAS integrates three complementary detection algorithms: the classical image-processing method CS-TRD and two deep-learning approaches, DeepCS-TRD and INBD. The interface allows users to refine automatic detections, remove false positives, and manually add missing rings. It also computes dendrochronological metrics such as earlywood and latewood areas, ring perimeter, equivalent ring width, and custom path-based ring-width measurements. TRAS was evaluated on 18 expertly annotated Pinus taeda L. cross-section images. DeepCS-TRD achieved the best automatic detection performance, with an F-score of 81.0% and precision of 86.4%. Automatic detection reduced the required manual correction effort to approximately 20% of ring boundaries. For one-dimensional ring-width measurements, TRAS showed excellent agreement with CooRecorder ($r > 0.99$). Common detection errors, such as jump propagation or false positives near knots, were easily corrected through the postprocessing interface. TRAS provides a flexible and reproducible solution for tree-ring analysis on Windows, macOS, and Linux. Code is available at the https://hmarichal93.github.io/tras.

Problem

• tree ring marking
• dendrometry
• dendrochronology
• manual tracing
• large image datasets

Innovation

• tree-ring detection
• deep learning
• interactive software
• dendrochronology
• automatic delineation