Abstract
In recent years, due to the decreasing number of skilled engineers in the civil engineering field, there is an increasing demand for further efficiency improvements in tasks such as geological surveys. The quality evaluation of cores in boring surveys relies on visual observation and measurement by skilled engineers based on multiple evaluation indicators, such as maximum core length and Rock Quality Designation (RQD). Moreover, conventional automation methods have been limited to recognition through image binarization processing, requiring parameter adjustments depending on the imaging environment and geological variations. This study focuses on maximum core length and RQD, which have relatively clear quantitative criteria and can be determined from images. As a generalizable automatic measurement method that does not require additional training, usage of the features of normal maps obtained from an image-based foundation model is proposed. To verify the effectiveness of the proposed method, accuracy evaluations is conducted by using practical industry standards (maximum core length: MSE is 3 or less, RQD: MSE 10 or less) as evaluation criteria. The results confirmed the feasibility of automatic measurement within practical application standards.
