Vision Based Displacement Detection for Stabilized UAV Control on Cloud ServerReport as inadecuate

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Mobile Information Systems - Volume 2016 2016, Article ID 8937176, 11 pages -

Research Article

Department of Computer Science and Engineering, Konkuk University, Neungdong-Ro, Gwangin-Gu, Seoul 143-701, Republic of Korea

Smart Mobility Research Group ETRI, 218 Gajeong-ro, Yuseong-gu, Daejeon 34129, Republic of Korea

Received 4 June 2016; Accepted 28 July 2016

Academic Editor: Nik Bessis

Copyright © 2016 Hyeok-June Jeong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Nowadays, image processing solution is used in many fields such as traffic information systems and illegal intrusion detection systems. Now, to assist with the control of camera-equipped devices, appropriate image processing techniques are needed for moving rather than fixed observers. For achieving this goal, an algorithm should derive the desired results quickly and accurately; thus, this paper considers two characteristics: functional performance reliability and temporal performance efficiency. Reliability means how well the desired results can be achieved, and efficiency means how quickly the result can be calculated. This paper suggests an optimized real-time image algorithm based on the integration of the optical flow and Speeded-Up Robust Features SURF algorithms. This algorithm determines horizontal or vertical movement of the camera and then extracts its displacement. The proposed algorithm can be used to stabilize an Unmanned Aerial Vehicle UAV in situations where it is drifting due to inertia and external forces, like wind, in parallel. The proposed algorithm is efficient in achieving drift stabilization by movement detection; however, it is not appropriate for image processing in small UAVs. To solve this problem, this study proposes an image processing method that uses a high-performance computer.

Author: Hyeok-June Jeong, Jeong Dan Choi, and Young-Guk Ha



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