Image Based Identification and Localizing of Drones
Keon Young Yi, Kisung Seo · The Transactions of The Korean Institute of Electrical Engineers · 2020
As commercial drones have been widely used, concerns for collision accidents with people and invading secured properties are emerging. The identification and localization drone is a challenging problem. DroneTracker, commercially available SW, for two dones with Inspire2, Phantom4Pro is tested but the performances of identification and localization are very low. We have suggest a image processing based identification and localization method for drones using the relationship between drone image size and real distance. It is tested for same experimental environments. We have obtained not only clear identification of each drone, but much superior performances of identification and localization. Furthermore the exactness of tracking is very close to the original tracking path.