<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/10012118" mdate="2021-06-05 00:00:00"> <author>Jorge Martinez-Garcia and Ingrid Stelzner and Joerg Stelzner and Damian Gwerder and Philipp Schuetz</author> <title>Image Processing Approach for Detection of ThreeDimensional TreeRings from XRay Computed Tomography</title> <pages>414 - 417</pages> <year>2021</year> <volume>15</volume> <number>7</number> <journal>International Journal of Computer and Information Engineering</journal> <ee>https://publications.waset.org/10012118.pdf</ee> <url>https://publications.waset.org/vol/175</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>Treering analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator&amp;amp;rsquo;s experience. This work presents an image processing approach to detect the whole 3D treering structure directly from Xray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected treering edges throughout the measured image stack and is validated on Xray computed tomography data taken from six wood species. </abstract> <index>Open Science Index 175, 2021</index> </article>