Path planning for rescue vehicles via segmented satellite disaster images and GPS road map - Korkmaz, S. Aytac; Poyraz, M. (Institute of Electrical and Electronics Engineers Inc., 2017)
One of the most important issues after so many disasters, besides communication determine the damage caused by the disaster areas to reach a moment ago. The emergency rescue teams established for this purpose by making plans to take action on realistic maps are required. Not just as an ambulance during rescue, vehicles in a variety of business machines correct route to take on the road safely. In this study, the image taken before and after the disaster has been segmented. Each segment with one another emerging feature-based compared using statistical methods and information theory. Then we get a measure to path planning using Kullback-leibler distance. Consequently, create a new hazard map is obtained. This map is compared with using the existing path in a city map. In this way, the shortest and safest route to the destination is obtained. © 2016 IEEE.
9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016 -- 15 October 2016 through 17 October 2016 -- Datong -- 126492
Keywords: disaster detection and classification; Kullback-Leibler; optimum road estimation; Rescue vehicles; Road Map; satellite disaster images segmentation