Figure 2. The content of the bounding boxes calculated using the YOLO algorithm can be seen in (a)-(c) for three different cases. Color threshold segmentation has been used making it easier to locate the paint damages in the bounding boxes. Note that a mask is added to the image of TP to cover the identity of the owner.
AI sometimes falsely finds paint damage on other surfaces such as water or other TPs. An example of this is shown in Figure 3 (a) below. Here the small bounding box is placed on the TP of interest while the larger bounding box is placed on a distant TP. Only the content of the bounding box on the center TP should be mapped to the 3D model of the tower. Masking the images can solve this problem if the TPs are not placed too close to each other, this condition is always met when the TPs are placed in the wind farm. The images with paint damage have been masked using three steps. Segmentation using the color threshold approach is applied to the image. The largest coherent area is then found in the corresponding binary mask. This binary mask is then applied to the original images.
The physical asset here the TP will always be the biggest item in the images. The photogrammetry technique requires that this is the case. If this is not the case the image will be discarded. If the asset has different colors then the color threshold approach cannot be used. A segmentation candidate could in this case be a graph-based segmentation technique like lazy-snapping which makes it possible to segment an image into foreground and background regions. The foreground will here be the transition piece. Different segmentation techniques should be selected based on the specific circumstances. However, the color threshold segmentation technique is very suitable for paint damage detection cases because only objects with a specific color are of interest and it is therefore not important that objects with other colors get removed using the color threshold segmentation technique.
The original image with two YOLO bounding boxes is shown in Figure 3 (a) while the masked image is shown in Figure 3 (b). The first bounding box is placed in the dark area of the masked image and the corresponding pixels will not be mapped to the TP. Only the correctly placed bounding box pixels will be mapped to the TP. This is done using an approach discussed in the following section. All images with paint damage should be masked using this approach. Depending on the light conditions during the capture of the drone images it can be necessary to calculate and use a few different binary masks on the original images.