عنوان مقاله [English]
In order to establish a system for managing road pavement, it is mandatory to prepare information components based on various perspectives of pavement management. One of the most important information components in these systems is quality assessment regarding road pavement status. Apart from causing vehicle depreciation and damage, maintenance costs, and reducing the useful lifespan of the pavement structure, road pavement failures also lead to accidents and reduce road safety. Bearing in mind that the most important surface damages in road pavement are related to cracks with longitudinal, transverse, oblique, alligator and block types, and as such cracks and defect can be visually and non-destructively assessed and evaluated, imaging-based approaches and techniques can provide details such as the type of defect, its severity, extent, and location and prove to be highly useful. UAV has been proposed as a complementary approach aimed at providing information on defects caused by cracks in the country road pavement management system. According to the author, the output of UAV products will significantly improve if the system parameters are adjusted. Consequently, through presenting a procedure to investigate the optimal parameters in the design of a UAV network, further, attempts were made for the implementation of an automated algorithm based on image processing operations & classifier decision tree which is independent of scale and image dimensions. Hence, after removing the road edges and determining the asphalt area, a pixel detection operation was carried out to reveal the cracks. An accuracy of 96% was determined for the orthophotomosaic.