# Detection of Pest Feeding Traces on Industrial Wood Surfaces with 3D Imaging
## 3 Results  
The recorded three-dimensional image was pre-filtered to remove noise caused by the scattering of the laser beam on the wood surface. The image noise was removed using a median filter with a 3 \(\times\) 3 matrix structure element. Morphological analysis was performed on the resulting image using an erosion operation. As a result of applying this transformation, the measurement points located directly at the edges of each hole were  
Figure 3: 3D images acquired with different resolutions, as follows: (**a**) image of the laser line on the wood surface used for profile generation—height profile is calculated based on laser line position in each column; (**b**) image acquired with a resolution of 0.125 mm/pixel (fully visible hole areas); (**c**) image acquired with a resolution of 0.2 mm/pixel; (**d**) image acquired with a resolution of 0.25 mm/pixel; and (**e**) image acquired with a resolution of 0.5 mm/pixel (some holes missing due to low resolution). directly assigned to the hole (Figure 4a). In this way, the surface area of each hole was increased by the points that formed the edge of the hole. The results of the transformations performed can be seen in the three-dimensional image shown in Figure 4b. Figure 4 shows the hole regions with precise edges, allowing the x- and y-coordinates of the position of each hole to be identified. The image was described by a grid of points with three coordinates. For a valid wood surface, the z-coordinate of each point describes the actual value of the surface height. For points inside the hole, the height of each point is equal to 0, i.e., Pi (xi, yi, 0). A segmentation based on the height analysis of the points in the three-dimensional image identifies the areas associated with the surface damage. Regardless of the shape of the defect, the same method of defect localisation was used for regular (circular) and irregular (elongated) holes. A calculation of the centre of gravity of the hole, i.e., the defect visible on the surface, was used. The results of this analysis are presented in Figure 4b. Using this method, it was possible to locate the centre of gravity of a defect visible on the surface, regardless of its shape and dimensions. The coordinates of the position of the centre of each area were determined using the Centre of Gravity (COG) algorithm by analysing a set of points of the hole (Figure 5). By analysing each wormhole separately, the position of the region's centre of gravity was calculated from the x- and y-coordinates of the points P that formed the region. Figure 4: Three-dimensional image of the wood surface: (**a**) regions of the edges detected around each hole; (**b**) three-dimensional surface of the wood with visible wormholes after the filtering operation and hole position identification. Figure 5: Three-dimensional image of the wood surface: (**a**) wood surface with visible wormhole; (**b**) exemplary description of the wormhole using measurement points. Using the coordinates of the position of the points that formed the region, the position of the centre of gravity was determined using the following relationship:  
\[COG_{X}=\frac{1}{P}\sum_{i=1}^{P}P_{xi} \tag{4}\]  
\[COG_{Y}=\frac{1}{P}\sum_{i=1}^{P}P_{yi} \tag{5}\]  
where:  
\(P\)--the number of points forming the affected area,  
\(P_{xi}\)--x-coordinate of point \(P_{i}\),  
\(P_{yi}\)--y-coordinate of point \(P_{i}\). Based on the three-dimensional image analysis, a set of geometric parameters was determined, describing each area of the detected defect. The perimeter of the defect area was also determined, in addition to three parameters for diameter, i.e., the minimum diameter, maximum diameter, and average diameter measured for the holes. In addition, the perimeter of the defect area and the ovality parameter were calculated for each region. All parameters were determined in the image coordinate system and given in units corresponding to the number of measurement points. Figure 6a shows the location of the damaged areas.