Fuzzy-Based Automatic Landmark Recognition in Aerial Images Using ORB for Aerial Auto-localization

Aerial navigation based on computer vision is a subject in constant development. It aims to identify the localization of an Unmanned Aerial Vehicle based on aerial images captured during flight. This paper employs a fuzzy-based application to identify landmarks, using the ORB algorithm, which uses descriptors for the neighborhood of keypoints to identify specific registered objects on a scene. In Addition to the keypoint matching from ORB, a fuzzy system is used to analyze each match, in order to guarantee the proper identification of the landmark.

[1]  E. Badreddin,et al.  A hybrid localization approach for UAV in GPS denied areas , 2011, 2011 IEEE/SICE International Symposium on System Integration (SII).

[2]  D. B. Davis,et al.  Intel Corp. , 1993 .

[3]  Hyukseong Kwon,et al.  Robust mobile ground target localization using ground image features with UAV position compensation techniques , 2012, 2012 12th International Conference on Control, Automation and Systems.

[4]  Taskin Padir,et al.  Design and implementation of an Intelligent Portable Aerial Surveillance System (IPASS) , 2013, 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA).

[5]  Wolfgang Hübner,et al.  Monocular Camera Trajectory Optimization using LiDAR data , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[6]  Qiong-hai Dai,et al.  Vision aided unmanned aerial vehicle autonomy: An overview , 2010, 2010 3rd International Congress on Image and Signal Processing.

[7]  Taro Suzuki,et al.  Vision based localization of a small UAV for generating a large mosaic image , 2010, Proceedings of SICE Annual Conference 2010.

[8]  Se-Young Oh,et al.  Efficient visual salient object landmark extraction and recognition , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[9]  Gary R. Bradski,et al.  ORB: An efficient alternative to SIFT or SURF , 2011, 2011 International Conference on Computer Vision.

[10]  Xueyuan Guan,et al.  A GPU accelerated real-time self-contained visual navigation system for UAVs , 2012, 2012 IEEE International Conference on Information and Automation.

[11]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[12]  Xuqiang Zhao,et al.  Vision based ground target tracking for rotor UAV , 2013, 2013 10th IEEE International Conference on Control and Automation (ICCA).

[13]  Peter W. Gibbens,et al.  Efficient Terrain-Aided Visual Horizon Based Attitude Estimation and Localization , 2015, J. Intell. Robotic Syst..

[14]  Taro Suzuki,et al.  Development of a SIFT based monocular EKF-SLAM algorithm for a small unmanned aerial vehicle , 2011, SICE Annual Conference 2011.