ENHANCED ALGORITHMS TO EXTRACT DECAY FORMS OF CONCRETE INFRASTRUCTURES FROM UAV PHOTOGRAMMETRIC DATA

Nowadays, inspection and maintenance of infrastructures is one of the most crucial issues to be faced. The structural performances should be constantly checked, considering that especially ageing stock and extreme weather events deteriorate the network infrastructure over time. However, economic reasons and the practical difficulty of carrying out a targeted inspection makes the detection a major challenge. In most of the western countries, a high percentage of infrastructures has reached and exceeded the nominal life, so the detection plays a fundamental role for their proper functioning. In this paper, experimental algorithms were tested to extract the decay forms on a portion of concrete pillar. These algorithms were applied on a metric digital image, obtained by photogrammetric output. The finally accuracy was calculated considering as ground truth the visual inspection performed by a concrete expert and the confusion matrices, the overall accuracy and the kappa-coefficient were evaluated. Then, a comparison with existing algorithms was made using the same methodology. The stacking of the original RGB image with two of the experimental algorithms could increase the accuracy up to 5%, while the common ones did not produced significant improvements. The final purpose of this work was to propose a semi-automatic/automatic procedure to detect concrete decay forms and, therefore, help the infrastructure management. The awareness is essential to provide the best practices to ensure safety and adequate performance over time.