[IPOL announce] new article: Ant Colony Optimization for Estimating Pith Position on Images of Tree Log Ends
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Sun Dec 11 20:29:53 CET 2022
A new article is available in IPOL: https://www.ipol.im/pub/art/2022/338/
Rémi Decelle, Phuc Ngo, Isabelle Debled-Rennesson, Frédéric Mothe, and
Fleur Longuetaud,
Ant Colony Optimization for Estimating Pith Position on Images of Tree
Log Ends,
Image Processing On Line, 12 (2022), pp. 558–581.
https://doi.org/10.5201/ipol.2022.338
Abstract
The pith location is one of the most important features to detect in
order to determine the quality of wood. Indeed, it allows to extract
other important features. In this paper, we address the problem of pith
detection on images of wood cross-sections. Taking such images can be
done at little cost and with a high resolution. However, contrary to
computed tomographic images, digital images exhibit disturbances like
sawing marks, dirt or ambient light variations which make difficult the
image analysis. Few studies have focused on such images. Furthermore
these studies do some prior segmentation or cropping before the
detection. We propose an approach for estimating the pith location
without any requirements. Our method is based on an ant colony
optimization algorithm. It is a probabilistic approach for solving this
task. We validate our algorithm on images of Douglas fir captured after
harvesting. The efficiency of this algorithm has been demonstrated by
performance comparisons with other approaches. Experiments show an
accurate and fast estimation and the algorithm could be used in real
time, at sawmill environment or in forest, with a smartphone.
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