Segmentation of Digital Images of Aerial Photography

For today, autonomous UAVs are a combination of artificial intelligence, mechanical devices, and navigational instruments. To save computing resources and improve the quality of their navigation, motion control systems, recognition, etc., real-time UAV's video has to be preprocessed by segmentation or clustering algorithms. In this work, the analysis of parameters of effective graph-based (EGB) and pyramidal segmentation algorithms (PSA) was obtained for digital images of aerial photography. The authors used RGB, Lab, and HSV (BHS) color models. According to the results of testing EGB algorithm is faster, but its result of segmentation is ordinary. Whereas, PSA produces a result that is closer to human perception but its disadvantage is a long processing time. Authors recommended Lab and HBS formats of image, since their segmentation results are more effective than, for example, at RGB.