Automatic Tree Ring Detection using Jacobi Sets

TL;DR

This paper introduces automated methods combining image processing and topological data analysis to detect tree rings and the pith in 3D X-ray CT images, reducing manual effort and improving accuracy.

Contribution

The paper presents novel automated techniques for locating the pith and ring boundaries in tree disks using topological data analysis, outperforming existing methods.

Findings

Better ring counting accuracy than existing automatic methods

Effective pith and boundary detection in 3D CT scans

Parameter optimization reduces detection errors

Abstract

Tree ring widths are an important source of climatic and historical data, but measuring these widths typically requires extensive manual work. Computer vision techniques provide promising directions towards the automation of tree ring detection, but most automated methods still require a substantial amount of user interaction to obtain high accuracy. We perform analysis on 3D X-ray CT images of a cross-section of a tree trunk, known as a tree disk. We present novel automated methods for locating the pith (center) of a tree disk, and ring boundaries. Our methods use a combination of standard image processing techniques and tools from topological data analysis. We evaluate the efficacy of our method for two different CT scans by comparing its results to manually located rings and centers and show that it is better than current automatic methods in terms of correctly counting each ring and its location. Our methods have several parameters, which we optimize experimentally by minimizing edit distances to the manually obtained locations.