Rust Detection

The aim is use a data driven approach to evaluate corrosion spread across an asset. The input data is a large dataset of high quality dense image data. The dataset variability is high (e.g. different lighting conditions, perspective, scale, etc), and it is initially unlabelled. Each image’s location and orientation is available and is referenced to a fixed reference frame. Corroded areas need to be identified in each image. Information from the multi-perspective images also need to combined to present a unified result on the distribution of corrosion across the asset. The output is the percentage of corrosion coverage on the asset surface.