Abstract
This paper introduces an algorithm for real-time line detection and tracking utilizing the Graphic Processing Units (GPUs) for UAV’s vision-based hovering control system. We concentrate that there are many of lines where UAV can fly, and extract meaningful line to grasp of vehicle’s attitude. We implemented image processing techniques on GPUs for real-time performance because detection and tracking of lines need huge computational resources. Experiments show affordable frame throughput that our approach is feasible in real flight.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mills, S., Pridmore, T., Hills, M.: Tracking in a Hough Space with the Extended Kalman Filter
Choi, K., Min, K., Lee, S., Park, W., Seo, Y., Hong, Y.: Lane Tracking in Hough Space Using Kalman filter
Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.: An Efficient k-Means Clustering Algorithm: Analysis and Implementation. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7) (July 2002)
R.O. Duda, P.E. Hart: Use of Hough Transformation to detect lines and curves in pictures (April 4, 2003)
Welch, G., Bishop, G.: An Introduction to the Kalman Filter, Department of Computer Science, University of North Carolina (2006)
Chen, S., Jiang, H.: Accelerating the Hough Transform with CUDA on Graphics Processing Units, Department of Computer Science, Arkansas State University
Gómez-Luna, J., González-Linares, J.M., Benavides, J.I., Zapata, E.L., Guil, N.: Parallelization of the Generalized Hough Transform on GPU, Computer Architecture and Electronics Department, University of Córdoba, Córdoba, Spain
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vladimir, T., Jeon, D., Kim, DH. (2014). A Vision-Based Robust Hovering Control System for UAV. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_52
Download citation
DOI: https://doi.org/10.1007/978-3-642-40675-1_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40674-4
Online ISBN: 978-3-642-40675-1
eBook Packages: EngineeringEngineering (R0)