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ORIGINAL PAPER
Imaging fungal infections on wood surfaces based on vision system
1
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Poland
These authors had equal contribution to this work
Submission date: 2023-11-21
Final revision date: 2024-11-19
Acceptance date: 2024-12-02
Online publication date: 2025-02-26
Corresponding author
Andrzej Sioma
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Al. Mickiewicza 30, 30-059, Krakow, Poland
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Al. Mickiewicza 30, 30-059, Krakow, Poland
KEYWORDS
TOPICS
wood mechanical and chemical technology, inter alia, sawmilling, composite wood products, wooden construction, furniture making, wood pulp, paper makingforestry: harvesting and wood quality
ABSTRACT
The article discusses the method of imaging fungal infections on the surface of wood using a dedicated vision system. Fungal infections develop on the surface of wood during transport and storage. In the production process, qualitative sorting of wood is carried out based on presence of infections on surfaces. Some infections are clearly visible, e.g. in the form of black blemishes. However, many infections are poorly visible or invisible to operators sorting material. The paper discusses a vision system that enables imaging defects occurring on wood that are invisible to the human eye. Examples of wood surface infections are presented. The developed concept of surface imaging using spectral illumination and a two-camera system is discussed. For the proposed system, the image sensors of the cameras and spectral characteristics of the illuminators are presented. Then, the configuration of the vision system was indicated, and the imaging resolutions for the selected example were determined. Examples of infection images recorded with the use of UV and RGB illuminators are presented. Image analysis was performed using intensity characteristics method for sample chosen images. The possibility of identifying infected areas using the intensity characteristics of the UV image and the RGB image was evaluated. The imaging results for selected ranges of electromagnetic radiation and selected infections recorded on the surface of wood are discussed. The possibility of observing and identifying infected areas invisible to the human eye has been confirmed.
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