Cobble edge detection algorithm based on digital image processing

Cobble size distribution (CSD) on the surface of a cobble bed is an important part of the river system, with important implications for river ecology and geomorphology. A digital image edge detection algorithm based on markers and detection lines is proposed to realize automatic statistics gathering of CSD. By making multiple detection lines outward from the markers, the cobble edge detection process of 2D images is transformed into a 1D space for analysis and processing. To correct the error detection points, an edge correction algorithm based on mutation point detection is designed. Simultaneously, a cobble edge reconstruction algorithm is proposed to restore covered cobble edges. The results of a verification experiment and comparative analysis indicate that the relative error of D-50, which was estimated by the algorithm in our study, is 3% in the laboratory and 8% in the field. The proposed method is reliable for the estimation of CSD with grain size range of 5 to 50 cm. In conclusion, the proposed algorithm is suitable for river geomorphology research and physical habitat studies of cobble floodplains using an unmanned aerial vehicle for remote sensing photography.