Automatic Tree Ring Detection using Jacobi Sets
This work addresses the need for less manual effort in dendrochronology, but it is incremental as it builds on existing computer vision techniques with specific improvements.
The authors tackled the problem of automating tree ring detection from 3D X-ray CT images of tree disks, presenting novel methods for locating the pith and ring boundaries using image processing and topological data analysis, and showed that their method outperforms current automatic methods in correctly counting and locating rings.
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.