Binocular Vi sual Object Extraction for UAV Autonomous Take-off and Landing

This paper employs the Chan-Vese (CV) model into aircraft objective extraction for binocular stereo vision to enable autonomous take-off and landing of unmanned aerial vehicles. Fundamental principles of the CV model and the level set method are summarized as minimizing energy function. Eventually, a flying VA V objective extraction algorithm is proposed and developed by using the CV model. Two sets of VA V landing images are collected for validation. Experimental results show that the proposed algorithm can effectively extract the VA V target even with a complex background. Furthermore, the accuracy of localization is comparable with nGPS and it is better than that BRISK maximal response value algorithm.

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