Resumen
The advancement in digital image analysis methods has led to the development of various techniques, i.e., quantification of ballast gravel abrasion. In this study, the recognition rate of gravel aggregates has been significantly increased by improving the image analysis methods. The correlation between the track quality index (TQI), which is the standard deviation of vertical track irregularity and represents the condition of a high-speed railway, and the number of maintenance works was analyzed by performing an image analysis on the samples collected from various locations of a high-speed railway. The results revealed that roundness has the highest correlation with the TQI, whereas sphericity has the highest correlation with the number of maintenance works. The ballast replacement would be performed to improve maintenance efficiency if the abrasion of the ballast aggregates becomes approximately 10%.