[IPOL announce] new article: Ant Colony Optimization for Estimating Pith Position on Images of Tree Log Ends

[announcements about the IPOL journal]

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.