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Wood used in production processes can be infected by various fungi growing on its surface. The presence of fungi on the wood surface results from the method of storage, handling and transport of the wood. However, the presence of fungi on wood carries a high risk to the health of production operators and users. At the same time, it has a negative impact on the quality and durability of manufactured products. Because of the risks indicated, an attempt was made to develop an industrial, automated system for detecting fungal infections. This paper presents a vision method for detecting fungal infections on the wood surface. A description of the vision system using the laser triangulation method (LTM) to build a three-dimensional surface image is shown. The paper consists of an analysis of the imaging resolution and a description of the concept of using laser illuminator power selection for identifying fungal-infested surfaces. Imaging results for the selected wavelength of electromagnetic radiation are presented. Measurements and parameters describing the identified areas are shown. It was found that it is possible to choose imaging method parameters and laser illumination power allowing identification under industrial conditions of a fungus-infected region on a wood surface while using the image to determine product measurement parameters.

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This article presents a vision method of identifying and measuring wood surface parameters to detect defects resulting from errors occurring during machining. The paper presents the method of recording a three–dimensional image of the wood surface using the laser triangulation method. It discusses parameters related to imaging resolution and the impact of vision system configuration parameters on the measurement resolution and image acquisition time. For the recorded image, proposed algorithms detect defects like wade and bark at the board edges. Algorithms for measuring characteristic parameters describing the surface of the wood are presented. Validation tests performed using the prepared system in industrial conditions are provided and discussed. The proposed solution makes it possible to detect board defects in flow mode on belt conveyors operating at a speed of up to 1000 mm/s.