Rusty Detection Using Image Processing For Maintenance Of Stations

This study addresses the challenge of accurately seg-menting rusted areas on painted construction surfaces. A method leveraging digital image processing is explored to calculate the percentage of rust present on painted coatings. The proposed segmentation approach is based on the HSV color model. To equalize luminosity and mitigate the influence of illumination, a fundamental model of single-scale Retinex is applied specifically to the saturation component. Subsequently, the image undergoes further processing, involv-ing manual color filtering. This step is crucial for refining the identification of rusted regions. To enhance precision and filter out noise, the pixel areas selected through color filtering are subjected to the DBScan algorithm. This multi-step process aims to achieve a robust segmentation of rusted areas on painted construction surfaces, providing a valuable contribution to the field of corrosion detection and analysis.