Unsupervised Modular Adaptive Region Growing and RegionMix Classification for Wind Turbine Segmentation

ArXi:2601.04065v2 Announce Type: replace Reliable operation of wind turbines requires frequent inspections, as even minor surface damages can degrade aerodynamic performance, reduce energy output, and accelerate blade wear. Central to automating these inspections is the accurate segmentation of turbine blades from visual data. This task is traditionally addressed through dense, pixel-wise deep learning models. However, such methods demand extensive annotated datasets, posing scalability challenges. In this work, we