[IPOL announce] new article: CNN-based Method for Segmenting Tree Bark Surface Singularites
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Tue Jan 4 20:42:15 CET 2022
A new article is available in IPOL: http://www.ipol.im/pub/art/2022/369/
Florian Delconte, Phuc Ngo, Bertrand Kerautret, Isabelle
Debled-Rennesson, Van-Tho Nguyen, and Thiery Constant,
CNN-based Method for Segmenting Tree Bark Surface Singularites,
Image Processing On Line, 12 (2022), pp. 1–26.
https://doi.org/10.5201/ipol.2022.369
Abstract
The analysis of trunk shape and, in particular, the geometric structures
on the bark surface are of main interest for different applications
linked to the wood industry or biological studies. Bark singularities
are often external records of the history of the development of internal
elements. The actors of the forest sector grade the trees by considering
these singularities through standards. In this paper, we propose a
method using terrestrial LiDAR data to automatically segment
singularities on tree surfaces. It is based on the construction of a
relief map combined with a convolutional neural network. The algorithms
and the source code are available with an online demonstration allowing
to test the defect detection without any software installation.
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